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ABSTRACT: Infant intestinal development is immature and, thus, is vulnerable to bacterial and viral infections, which damage intestinal development and even induce acute enteritis. Numerous studies have investigated that lactoferrin (LF) has protective effects on the intestine and may play a role in preventing intestinal inflammation in infants. Lactoferrin is divided into 2 types, namely apo-LF and holo-LF, depending on the degree of iron saturation, which may affect its bioactivities. However, the role of LF iron saturation in protecting infant intestinal inflammation has not been clearly clarified. Therefore, in this study, young mice models with intestinal damage induced by lipopolysaccharides (LPS) in vivo and primary intestinal epithelial cells in vitro were constructed to enteritis injury in infants for investigation. The apo-LF and holo-LF were subsequently applied to the mouse models to investigate and compare their levels of protection in the intestinal inflammatory injury, as well as to identify which LF was most active. Moreover, the specific mechanism of the LF with optimal iron saturation was further investigated through Western blot assay. Results demonstrated that disease activity index, shortened length of colon tissue, and histopathological score were significantly decreased in the apo-LF group compared with those of the LPS group and the holo-LF group. In the apo-LF group, the concentration of LPS in the intestinal tract and the number of gram-negative bacteria colonies decreased significantly and the expression levels of proinflammatory factors in the colon tissue were downregulated, in comparison with those in the LPS group. The findings of this study thus verify that apo-LF can significantly alleviate enteritis injury caused by LPS, through regulating the PPAR-γ/PFKFB3/NF-κB inflammatory pathway.

The edge coherent mode (ECM) is considered a highly attractive pedestal mode because it extends the duration of edge-localized modes and increases particle and impurity transport without significantly affecting energy transport. Moreover, it operates compatibly with high-performance plasma discharges. The ECM can also be detected using Langmuir probes on the divertor target plate, indicating that it extends from the pedestal region into the SOL and resulting in a connection to the divertor target plate via magnetic field lines. In this work, the distribution of ECM on divertor target plates is investigated by analyzing 215 upper single null discharges on the EAST tokamak. The coherence analysis of plasma fluctuations between the electron cyclotron emission signal in the pedestal region of the outer midplane and the ion saturation current measured by Langmuir probes in the divertor region reveals that the ECM is hardly detected by the divertor probe close to the outer strike point but can be observed at far SOL. This finding indicates the presence of an ECM quiescent region near the SOL on the divertor plate, and the extent of the quiescent region in the poloidal flux coordinate (Δ) has been statistically analyzed. A pronounced relationship between Δ and triangularity ( δ ) has been observed, that is Δ increasing with δ . Further analysis reveals that this relationship can be attributed to the average magnetic shear in the SOL. This result is consistent with the physical picture, which states that strong magnetic shear close to X -point significantly squeezes the cross-section of flux tubes down to scales dominated by collisions.

Coccidiosis is a major disease caused by various Eimeria species in rabbits. The aim of the present study was to investigate the haematological and pathological changes in rabbits infected with E. magna. Moreover, the localisation of coccidial antigens was examined in the intestines of rabbits with two kinds of serum as primary antibodies. In the present study, forty-five 28-day-old weaned rabbits were randomly divided into three groups and reared in three separate places. Group A was infected with 20×103 sporulated oocysts of E. magna, group B was only used to produce anti-E. intestinalis serum by infecting them with 3×103 sporulated oocysts of E. intestinalis, and group C was designated as the control group. According to histopathological evaluation of group A, the epithelial cells of the jejunum and ileum were parasitised with a large number of oocysts and other stages of E. magna. The haematological results showed that red blood cell counts, haemoglobin counts, haematocrit levels and the percentage of lymphocytes were significantly decreased in group A compared with group C (P

Band registration is one of the most critical steps in the production of multi/hyperspectral images and determines the accuracy of applications directly. Because of the characteristics of imaging devices in some multi/hyperspectral satellites, there may be a time difference between bands during push-broom imaging, which leads to displacements of moving clouds with respect to the ground. And a large number of feature points may gather around cloud contours due to the high contrast and rich texture, resulting in building a transformation more suitable for moving clouds and making ground objects ghosted and blurred. This brings a big challenge for registration methods based on feature extraction and matching. In this paper, we propose a novel coarse-to-fine band registration framework for multi/hyperspectral images containing moving clouds. In the coarse registration stage, a cloud mask is generated by grayscale stretching, morphology and other operations. Based on this mask, a coarse matching of cloud-free regions is performed to eliminate large misalignment between bands. In the refinement stage, low-rank analysis and RASL (Robust Alignment by Sparse and Low-rank decomposition) are used to optimize the rank of coarse results to achieve fine registration between bands. After experiments on a total of 102 images (83 cloudy images and 19 cloud-free images with all 32 bands) from Zhuhai-1 hyperspectral satellite, our method can achieve a registration accuracy of 0.6 pixels in cloudy images, 0.41 pixels in cloud-free images, which is enough for subsequent applications.

Current popular deep neural networks for semantic segmentation are almost supervised and highly rely on a large amount of labeled data. However, obtaining a large amount of pixel-level labeled data is time-consuming and laborious. In remote sensing area, this problem is more urgent. To alleviate this problem, we propose a novel semantic segmentation neural network (S4Net) based on semi-supervised learning by using unlabeled data. Our model can learn from unlabeled data by consistency regularization, which enforces the consistency of output under different random transforms and perturbations, such as random affine transform. Thus, the network is trained by the weighted sum of a supervised loss from labeled data and a consistency regularization loss from unlabeled data. The experiments we conducted on DeepGlobe land cover classification challenge dataset verified that our network can make use of unlabeled data to obtain precise results of semantic segmentation and achieve competitive performance when compared to other methods.

Cloud detection is a vital preprocessing step for remote sensing image applications, which has been widely studied through Convolutional Neural Networks (CNNs) in recent years. However, the available CNN-based works only extract local/non-local features by stacked convolution and pooling layers, ignoring global contextual information of the input scenes. In this paper, a novel segmentation-based network is proposed for cloud detection of remote sensing images. We add a multi-class classification branch to a U-shaped semantic segmentation network. Through the encoder-decoder architecture, pixelwise classification of cloud, shadow and landcover can be obtained. Besides, the multi-class classification branch is built on top of the encoder module to extract global context by identifying what classes exist in the input scene. Linear representation encoded global contextual information is learned in the added branch, which is to be combined with featuremaps of the decoder and can help to selectively strengthen class-related features or weaken class-unrelated features at different scales. The whole network is trained and tested in an end-to-end fashion. Experiments on two Landsat-8 cloud detection datasets show better performance than other deep learning methods, which finally achieves 90.82% overall accuracy and 0.6992 mIoU on the SPARCS dataset, demonstrating the effectiveness of the proposed framework for cloud detection in remote sensing images.

Cultivated land resources are the basic production factors that carry human survival and economic development. Exploring the relationship between cultivated land change and economic development has become a hot issue for scholars.in this paper,The methods of regression analysis, land use elastic coefficient method, location entropy are used to empirically describe the relationship between cultivated land change and economic development.The results show: Since the 20th century, the change of cultivated land area has experienced three distinct stages of change, showing a process of recovery, decline, and steady evolution in Henan Province. The per capita cultivated land area is characterized by an upward trend, and the per capita cultivated land area is increasing year by year. In general, the intensive use of cultivated land in Henan Province is still not high, but the momentum of a sharp decline in cultivated land is basically controlled. The change of cultivated land area and economic development showed a four-time curve fitting relationship, which indicates that the path dependence of economic development on cultivated land occupation still exists, and cultivated land supports the rapid development of economy.The research results of the relationship between cultivated land change and economic development by using location entropy show that the spatial layout of the urban area is less than 0, and the regularity is not strong.The location where the location entropy is between 0–1 is mainly located in the central part of Henan Province;The cities with location entropy greater than 1 are mainly located in the eastern part of Henan.

By combining the X-mode polarized lower and upper cut-off reflections obtained from the density profile reflectometer, we have successfully attained a comprehensive density profile spanning from the edge to the core region in pellet injection (PI) experiments on EAST. During the homogenization process after PI on EAST, an innovative method was introduced to quantify the local density increase. This approach employed the distinctive ‘dual-reflection’ phenomenon observed in the EAST microwave reflectometer, encompassing measurements of both the X-mode lower and upper cut-off frequencies. Furthermore, experimental investigations were carried out on EAST to comprehensively explore the parallel and poloidal expansion of the high-density pellet cloud. Notably, this study marks the first instance of measuring expansion velocities of pellet materials in both parallel and poloidal directions on EAST. A comparative analysis was performed initially between these experimental measurements and simulation results obtained from the HPI2 code, marking a pivotal stride towards enhancing its applicability in EAST.

Traditional direction-of-arrival (DOA) estimation techniques perform Nyquist-rate sampling of the received signals and as a result they require high storage. To reduce sampling ratio, we introduce level-crossing (LC) sampling which captures samples whenever the signal crosses predetermined reference levels, and the LC-based analog-to-digital converter (LC ADC) has been shown to efficiently sample certain classes of signals. In this paper, we focus on the DOA estimation problem by using second-order statistics based on the LC samplings recording on one sensor, along with the synchronous samplings of the another sensors, a sparse angle space scenario can be found by solving an $ell_1$ minimization problem, giving the number of sources and their DOA's. The experimental results show that our proposed method, when compared with some existing norm-based constrained optimization compressive sensing (CS) algorithms, as well as subspace method, improves the DOA estimation performance, while using less samples when compared with Nyquist-rate sampling and reducing sensor activity especially for long time silence signal.

Two types of hairpin RNA (hpRNA) constructions were designed using a chimeric gene formed from two genes, the coat protein (CP) gene or the silencing suppressor gene, from the Cucumber mosaic virus (CMV) and the Potato virus Y (PVYN), respectively; one type generated a single hairpin structure, whereas the other formed a two-hairpin structure. Four constructs, pDCPSH (double CP gene fragments, single hairpin), pDCPDH (double CP gene fragments, double hairpins), pHC2bSH (two silencing suppressor gene fragments, single hairpin), and pHC2bDH (two silencing suppressor gene fragments, double hairpins), were individually introduced into tobacco plants. A transcript analysis demonstrates that the small interference RNA (siRNA) processing efficiency was greater with the double-hairpin construct than with the single-hairpin construct, although the expression of their target genes were similar. A viral resistance assay shows that the transgenic tobacco plants effectively resisted a mixed infection of CMV and Potato virus Y (PVYN) and that pDCPDH exhibited the highest silencing efficiency. The accumulation of siRNA in the inoculated transgenic plants expressing different hairpin structures was similar. A genetic analysis reveals that viral resistance in the transgenic plants was stably inherited from the T0 to T1 generation. A transcript analysis and a viral resistance assay indicate that the double-hairpin structure of the same target sequences tended to produce more siRNA before the virus inoculation and thus strengthened RNA-mediated viral resistance.

Viral resistance can be effectively induced in transgenic plants through their silencing machinery. Thus, we designed nine short hairpin RNAs (shRNA) constructs to target nuclear inclusion protein b (NIb), helper component proteinase (HC-Pro), cylindrical inclusion protein (CI) and viral protein genome linked (VPg) genes of Potato virus Y (PVYN) and Tobacco etch virus (TEV-SD1). The shRNAs were completely complementary to the genes of PVYN, and contained 1-3 nt mismatches to the genes of TEV-SD1. To study the specificity of gene silencing in shRNA-mediated viral resistance, the constructs were introduced into tobacco plants. The results of viral resistance assay revealed that these nine kinds of transgenic tobacco plants can effectively induce viral resistance against both PVYN and TEV-SD1, and the shRNA construct targeting the NIb gene showed higher silencing efficiency. Northern blot and short interfering RNA (siRNA) analyses demonstrated that the viral resistance can be attributed to the degradation of the target RNA through the RNA silencing system. Correlation analysis of siRNA sequence characteristics with its activity suggested that the secondary structure stability of the antisense strand did not influence siRNA activity; 1 to 3 nt 5' end of the sense strand caused a significant effect on siRNA activity where the first base such as U was favourable for silencing; the base mismatch between the siRNA and the target gene may be more tolerated in the 5' end.

To induce virus resistance in tobacco and rice we constructed hairpin RNA expression system harbouring inverted repeat fragments of coat protein cDNA of Potato virus Y (PVY) or Rice stripe virus (RSV). These structures were driven by three promoters [cauliflower mosaic virus 35S (CaMV 35S), polyubiqutin gene of maize (Ubi), and Pharbitis nil leucine zipper gene (PNZIP)] which have different tissue-specific activity. PVY resistance ratios were 65.18, 24.33 and 83.54 % in transgenic tobacco plants harboring p35S-PVY, pUbi-PVY and pPNZIP-PVY. RSV resistance was 16.21, 28.61 and 29.33 % in transgenic rice plants harboring p35S-RSV, pUbi-RSV and pPNZIP-RSV. Northern blotting and GUS assay demonstrated that virus resistance levels were related to promoter activity. Therefore, choice of the more effective and tissue-specific promoter to reinforce transcription of hpRNAs will favour the cultivation of highly virusresistant transgenic plants.

In this study, 16 hairpin RNA (hpRNA) vectors were constructed, each harboring 50 bp viral RNA sequence as the stem. They all targeted the coat protein (CP) gene of Potato virus Y (PVY). Virus resistance assay revealed that hairpin constructs targeting the anterior 200 bp regions of the CP gene were unable to induce virus resistance, while the 12 hpRNA constructs targeting posterior 600 bp regions induced high virus resistance up to 77.78 %. Northern blot analysis revealed that 50 bp-length hpRNA constructs could be transcribed efficiently and processed into siRNAs; however, no correlation between siRNA accumulation and degree of antiviral defense was observed. Results presented here indicated that the middle and 3' end of the CP cDNA was important for hpRNA-mediated PVY resistance, improving the design of pathogen-derived hpRNA expression cassettes for transgenic plant against viruses.

Despite long-standing interest in the biogeochemistry of the Santa Barbara Basin (SBB), there are no direct rate measurements of different nitrogen transformation processes. We investigated benthic nitrogen cycling using in situ incubations with 15NO3- addition and quantified the rates of total nitrate (NO3-) uptake, denitrification, anaerobic ammonia oxidation (anammox), N2O production, and dissimilatory nitrate reduction to ammonia (DNRA). Denitrification was the dominant NO3- reduction process, while anammox contributed 0 %–27 % to total NO3- reduction. DNRA accounted for less than half of NO3- reduction except at the deepest station at the center of the SBB where NO3- concentration was lowest. NO3- availability and sediment total organic carbon content appeared to be two key controls on the relative importance of DNRA. The increasing importance of fixed N retention via DNRA relative to fixed N loss as NO3- deficit intensifies suggests a negative feedback loop that potentially contributes to stabilizing the fixed N budget in the SBB. Nitrous oxide (N2O) production as a fraction of total NO3- reduction ranged from 0.2 % to 1.5 %, which was higher than previous reports from nearby borderland basins. A large fraction of NO3- uptake was unaccounted for by NO3- reduction processes, suggesting that intracellular storage may play an important role. Our results indicate that the SBB acts as a strong sink for fixed nitrogen and potentially a net source of N2O to the water column.

Summary: Background: Insulin resistance (IR) is an important risk factor for multiple chronic diseases, increasing mortality and reducing life expectancy. The associations between emerging surrogates for IR, triglyceride-glucose index (TyG) and TyG-related indicators, with all-cause mortality and life expectancy in middle-aged and older patients in primary care are unclear. Methods: This study originated from the Polish primary care cohort LIPIDOGRAM2015, including patients aged ≥45 years. Baseline fasting triglycerides and fasting glucose were used to derive TyG. Other TyG-related indicators included TyG-adjusted body mass index (TyG-BMI), TyG-adjusted waist circumference (TyG-WC), TyG-adjusted waist-to-hip, and TyG-adjusted waist-to-height. In this longitudinal analysis, we assessed associations between TyG-related indicators with total all-cause mortality, premature (age at death ≤75 years) all-cause mortality and years of life lost (YLL). Findings: We included 10,688 patients (mean age 61.8 ± 9.3 years; 63.5% female). Cumulative total and premature all-cause mortality were 7.2% and 4.6%, respectively, during 5.7 years (IQR 5.6–5.7) of follow-up. Lowest (Q1) and highest quartile (Q4) of TyG-BMI and TyG-WC were associated with total all-cause mortality (second quartile [Q2]: reference; TyG-BMI: Q1: aHR 1.33, 95% CI 1.07–1.65, Q4: aHR 1.28, 95% CI 1.03–1.58; TyG-WC: Q1: aHR 1.44, 95% CI 1.14–1.82, Q4: aHR 1.29, 95% CI 1.04–1.59), similar results for premature all-cause mortality. Within age 45–80 years, compared with Q2 and third quartile, YLL were 4.49 and 5.46 years for TyG-BMI Q1 and Q4, respectively, 3.24 and 5.31 years for TyG-WC Q1 and Q4, respectively. Interpretation: TyG-BMI and TyG-WC demonstrated a U-shaped association with total and premature all-cause mortality. Low and high levels of TyG-BMI and TyG-WC were associated with reduced life expectancy. Despite the relatively short follow-up period, significant associations were still observed, but longer follow-up studies are required to further explore these relationships. Funding: Polish Lipid Association, College of Family Physician in Poland, Valeant in Poland.