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The important role of soil carbon pools in coping with climate change has become widely recognized. Moso bamboo (Phyllostachys pubescens) is an economically important bamboo species in South China; however, owing to factors such as rising labor costs and increasingly stringent environmental policies, Moso bamboo forests have recently been abandoned. The present study aimed to investigate the effects of abandonment on structural factors and soil organic carbon (SOC) stocks in Moso bamboo forests. We investigated Moso bamboo forests subjected to intensive management or abandonment for different durations and measured forest structural characteristics, mineral properties, soil nutrients, and other soil properties. Although abandonment did not significantly affect the height and diameter at breast height, it increased culm densities, biomass, and SOC stocks. The drivers of SOC stocks depended on soil depth and were mainly controlled by carbon decomposition mediated by soil properties. In the topsoil, mineral protection and soil total nitrogen (TN) exerted significant effects on SOC stocks; in the subsoil, soil TN was the main driver of SOC stocks. As the controlling factors of SOC stocks differed between the subsoil and topsoil, more attention should be paid to the subsoil. Overall, these findings refine our understanding of the structural characteristics and SOC stocks associated with Moso bamboo forest abandonment, serving as a reference for the follow-up management of these forests.

Weaning is a challenging period for piglets, characterized by stress-related growth checks, compromised immunity, and gut dysbiosis. Purslane (Portulaca oleracea L.), known for its rich content of antioxidants, has potential as a functional feed ingredient. This study investigates the effects of feeding fermented purslane (FP) on the growth performance, immune function, intestinal microbiota, and metabolic profiles of weaned piglets. Forty-eight weaned piglets were randomly divided into two groups, with eight pens in each group and three pigs in each pen: a control diet (CON group) and a diet supplemented with 0.20% FP (FP group). The experiment lasted 28 days. The results show that FP supplementation did not affect the average daily feed intake (ADFI) but significantly increased the average daily gain (ADG) during the initial 14 days post-weaning. FP supplementation decreased diarrhea occurrence, with a pronounced reduction from days 10 to 13 (p < 0.05). Immunologically, the FP group had a trend towards reduced serum IgA levels on day 14 (p < 0.10). Importantly, the serum concentrations of the pro-inflammatory cytokine IL-6 were significantly reduced on both days 14 and 28 post-weaning. The antioxidative analysis showed increased serum superoxide dismutase (SOD) and decreased catalase (CAT) activities on day 14 (p < 0.05). In addition, FP supplementation significantly decreased serum diamine oxidase (DAO) activity and D-lactate levels by day 28, indicating a potential improvement in gut integrity. Fecal microbiota assessment demonstrated a distinctive clustering of microbial communities between the FP and CON groups, with an increase in the abundance of Clostridium_sensu_stricto_1, Tyzzerella, and Prevotellaceae_NK3B31_group and a decrease in Lactobacillus, Bacillus, and Subdoligranulum in the FP group (p < 0.05). Functional predictions suggested that the relative abundance of microbial butyrate synthesis enzymes (EC 2.7.2.7 and EC 2.3.1.19) was significantly enhanced by FP treatment. This modulation was further corroborated by elevated fecal butyrate levels (p < 0.05). In summary, dietary supplementation with FP promotes early-growth performance and has beneficial effects on immune function and intestinal health in weaned piglets. The enhancements may be attributed to distinct microbiota compositional changes and targeted modulation of microbial butyrate metabolism, which are crucial for piglet post-weaning adaptation and overall health.

α-Synuclein (α-syn) can form oligomers, protofibrils, and fibrils, which are associated with the pathogenesis of Parkinson’s disease and other synucleinopathies. Both the lipid peroxidation product 4-oxo-2-nonenal (ONE) and agitation can induce aggregation of α-syn and phosphorylated α-syn. Thus, clarification of the characteristics of different α-syn species could help to select suitable aggregates for diagnosis and elucidate the pathogenesis of diseases. Here, we characterized ONE-induced wild-type (WT) α-syn aggregates (OW), ONE-induced phosphorylated α-syn (p-α-syn) aggregates (OP), agitation-induced α-syn preformed fibrils (PFF), and agitation-induced p-α-syn preformed fibrils (pPFF). Thioflavin T (ThT) dying demonstrated that OW and OP had fewer fibrils than the PFF and pPFF. Transmission electron microscopy revealed that the lengths of PFF and pPFF were similar, but the diameters differed. OW and OP had more compact structures than PFF and pPFF. Aggregation of p-α-syn was significantly faster than WT α-syn. Furthermore, OW and OP were more sodium dodecyl sulfate-stable and proteinase K-resistant, suggesting greater stability and compactness, while aggregates of PFF and pPFF were more sensitive to proteinase K treatment. Both ONE- and agitation-induced aggregates were cytotoxic when added exogenously to SH-SY5Y cells with increasing incubation times, but the agitation-induced aggregates caused cell toxicity in a shorter time and more p-α-syn inclusions. Similarly, p-proteins were more cytotoxic than non-p-proteins. Finally, all four aggregates were used as standard antigens to establish sandwich enzyme-linked immunosorbent assay (ELISA). The results showed that the recognition efficiency of OW and OP was more sensitive than that of PFF and pPFF. The OW- and OP-specific ELISA for detection of p-α-syn and α-syn in plasma samples of Thy1-α-syn transgenic mice showed that the content of aggregates could reflect the extent of disease. ONE and agitation induced the formation of α-syn aggregates with distinct biophysical properties and biomedical applications.

The engineering of tubes with surface corrugations is recognized as an effective method for enhancing heat transfer within the tube. Yet the impact of surface corrugation on the flow and heat transfer around the tube’s exterior remains inadequately explored. This study investigates the crossflow and heat transfer characteristics in banks of periodically inward-corrugated tubes using computational fluid dynamics. Numerical simulations were performed for both in-line and staggered tube arrangements, covering Reynolds numbers from 1000 to 10,000. The aim was to examine how various corrugation parameters affect heat transfer and flow dynamics in tube banks configured in both in-line and staggered layouts. The results show that the heat transfer and the pressure drop in crossflow across tube banks are substantially influenced by changes in corrugation parameters. Specifically, in the in-line arrangement, both the Nusselt number and Euler number decrease significantly as the corrugation height increases. In contrast, in the staggered arrangement, the Nusselt number and Euler number exhibit less variation in response to surface corrugation. A comparative analysis of performance criteria suggests that a staggered arrangement is more advantageous for improving thermal–hydraulic efficiency in crossflow through corrugated tube banks.

Benzene is the typical volatile organic compound (VOC) of indoor and outdoor air pollution, which harms human health and the environment. Due to the stability of their aromatic structure, the catalytic oxidation of benzene rings in an environment without an external energy input is difficult. In this study, the efficient degradation of benzene at room temperature was achieved by constructing Ag and Ni bimetallic active site catalysts (AgNi/BCN) supported on boron–carbon–nitrogen aerogel. The atomic-scale Ag and Ni are uniformly dispersed on the catalyst surface and form Ag/Ni-C/N bonds with C and N, which were conducive to the catalytic oxidation of benzene at room temperature. Further catalytic reaction mechanisms indicate that benzene reacted with ·OH to produce R·, which reacted with O2 to regenerate ·OH. Under the strong oxidation of ·OH, benzene was oxidized to form alcohols, carboxylic acids, and eventually CO2 and H2O. This study not only significantly reduces the energy consumption of VOC catalytic oxidation, but also improves the safety of VOC treatment, providing new ideas for the low energy consumption and green development of VOC treatment.

The hot spot extraction agent N,N,N′,N′-tetraoctyl-3-oxoglutaramide (TODGA) has the advantages of novelty, high efficiency and environmental protection in the separation of rare earths by tandem extraction. In this paper, the characteristic parameters for the separation of dysprosium, erbium, thulium and ytterbium ions in the TOGDA–kerosene/hydrochloric acid system for tandem extraction were calculated. Using a 10% TODGA–kerosene/5 mol·L−1 hydrochloric acid extraction system, the mixture containing Dy3+ 0.258 mol·L−1, Er3+ 0.252 mol·L−1, Tm3+ 0.248 mol·L−1 and Yb3+ 0.242 mol·L−1 can be separated by three separation steps, and four products of Dy3+, Er3+, Tm3+ and Yb3+ can be obtained. The purity of the four products was 99.80%, 99.20%, 99.70% and 99.70%, and the yields were 99.03%, 98.97%, 97.88% and 96.98%, in order. In this paper, the reasons were analyzed for the differences in the ability of the TODGA system to extract heavy rare earth ions (REEs) in terms of density functionality, complex structure and bond valence model. These will provide more basic data and guidance for the industrial application of TODGA.

Recently, light use efficiency (LUE) models driven by remote sensing data have been widely employed to estimate the gross primary productivity (GPP) of different terrestrial ecosystems at global or regional scales. Furthermore, the two-leaf light use efficiency (TL-LUE) model has been reported to improve the accuracy of GPP estimation, relative to the big-leaf MOD17 model, by separating the entire canopy into sunlit and shaded leaves through the use of constant clumping index estimation (Ω). However, ignoring obvious seasonal changes in the vegetation clumping index (CI) most likely results in GPP estimation errors since the CI tends to present seasonal changes, especially with respect to the obvious presence or absence of leaves within the canopy of deciduous vegetation. Here, we propose a TL-CLUE model that considers the seasonal difference in the CI based on the TL-LUE model to characterize general changes in canopy seasonality. This method composites monthly CI values into two or three Ω values to capture the general seasonal changes in CI while attempting to reduce the potential uncertainty caused during CI inversion. In theory, CI seasonality plays an essential role in the distribution of photosynthetically active radiation absorbed by the canopy (APAR). Specifically, the seasonal difference in CI values mainly considers the state of leaf growth, which is determined by the MODIS land surface phenology (LSP) product (MCD12Q2). Therefore, the one-year cycle (OYC) of leaf life is divided into two (leaf-off and leaf-on) or three seasons (leaf-off, leaf-scattering, and leaf-gathering) according to this MODIS LSP product, and the mean CI of each corresponding season for each vegetation class is computed to smoothen the uncertainties within each seasonal section. With these two or three seasonal Ω values as inputs, the TL-CLUE model by which the seasonal differences in CI are incorporated into the TL-LUE model is run and evaluated based on observations from 84 eddy covariance (EC) tower sites across North America. The results of the analysis reveal that the TL-LUE model widely overestimates GPP for most vegetation types during the leaf-on season, particularly during the growth peak. Although the TL-LUE model shows that the temporal characteristics of GPP agree with the EC observations in terms of general trends, the TL-CLUE model further improves the accuracy of GPP estimation by considering the seasonal changes in the CI. The result of GPP estimation from the TL-CLUE model shows a lower error (RMSE = 2.46 g C m−2 d−1) than the TL-LUE model (RMSE = 2.75 g C m−2 d−1) and somewhat decreases the eight-day GPP overestimation in the TL-LUE model with a constant Ω by approximately 9.76 and 8.970% when adapting three and two Ωs from different seasons, respectively. The study demonstrates that the uncertainty of seasonal disturbance in the CI, quantified by a standard deviation of approximately 0.071 relative to the mean CI of 0.746, is diminished through simple averaging. The seasonal difference in CI should be considered in GPP estimation of terrestrial ecosystems, particularly for vegetation with obvious canopy changes, where leaves go through the complete physiological processes of germination, stretching, maturity, and falling within a year. This study demonstrates the potential of the MODIS CI application in developing ecosystem and hydrological models.

Oxidative stress is the major incentive for intestinal dysfunction in weaned piglets, which usually leads to growth retardation or even death. Silybin has caught extensive attention due to its antioxidant properties. Herein, we investigated the effect of dietary silybin supplementation on growth performance and determined its protective effect on paraquat (PQ)-induced intestinal oxidative damage and microflora dysbiosis in weaned piglets. In trial 1, a total of one hundred twenty healthy weaned piglets were randomly assigned into five treatments with six replicate pens per treatment and four piglets per pen, where they were fed basal diets supplemented with silybin at 0, 50, 100, 200, or 400 mg/kg for 42 days. In trial 2, a total of 24 piglets were randomly allocated to two dietary treatments with 12 replicates per treatment and 1 piglet per pen: a basal diet or adding 400 mg/kg silybin to a basal diet. One-half piglets in each treatment were given an intraperitoneal injection of paraquat (4 mg/kg of body weight) or sterile saline on day 18. All piglets were euthanized on day 21 for sample collection. The results showed that dietary supplementation with 400 mg/kg silybin resulted in a lower feed conversion ratio, diarrhea incidence, and greater antioxidant capacity in weaned piglets. Dietary silybin enhanced intestinal antioxidant capacity and mitochondrial function in oxidative stress piglets induced by PQ. Silybin inhibited mitochondria-associated endogenous apoptotic procedures and then improved the intestinal barrier function and morphology of PQ-challenged piglets. Moreover, silybin improved intestinal microbiota dysbiosis induced by the PQ challenge by enriching short-chain fatty-acid-producing bacteria, which augmented the production of acetate and propionate. Collectively, these findings indicated that dietary silybin supplementation linearly decreased feed conversion ratio and reduced diarrhea incidence in normal conditions, and effectively alleviated oxidative stress-induced mitochondrial dysfunction, intestinal damage, and microflora dysbiosis in weaned piglets.

Understanding post-fire forest recovery is critical to the study of forest carbon dynamics. Many previous studies have used multispectral imagery to estimate post-fire recovery, yet post-fire forest structural development has rarely been evaluated in the Great Xing’an Mountain. In this study, we extracted the historical fire events from 1987 to 2019 based on a classification of Landsat imagery and assessed post-fire forest structure for these burned patches using Global Ecosystem Dynamics Investigation (GEDI)-derived metrics from 2019 to 2021. Two drivers were assessed for the influence on post-fire structure recovery, these being pre-fire canopy cover (i.e., dense forest and open forest) and burn severity levels (i.e., low, moderate, and high). We used these burnt patches to establish a 25-year chronosequence of forest structural succession by a space-for-time substitution method. Our result showed that the structural indices suggested delayed recovery following the fire, indicating a successional process from the decomposition of residual structures to the regeneration of new tree species in the post-fire forest. Across the past 25-years, the dense forest tends toward greater recovery than open forest, and the recovery rate was faster for low severity, followed by moderate severity and high severity. Specifically, in the recovery trajectory, the recovery indices were 21.7% and 17.4% for dense forest and open forest, and were 27.1%, 25.8%, and 25.4% for low, moderate, and high burn severity, respectively. Additionally, a different response to the fire was found in the canopy structure and height structure since total canopy cover (TCC) and plant area index (PAI) recovered faster than relative height (i.e., RH75 and RH95). Our results provide valuable information on forest structural restoration status, that can be used to support the formulation of post-fire forest management strategies in Great Xing’an Mountain.

The Yellow River Basin serves as a crucial ecological barrier in China, emphasizing the importance of accurately examining the spatial distribution of forest carbon stocks and enhancing carbon sequestration in order to attain “carbon peaking and carbon neutrality”. Forest patches have complex interactions that impact ecosystem services. To our knowledge, very few studies have explored the connection between these interactions and carbon stock. This study addressed this gap by utilizing complex network theory to establish a forest ecospatial network (ForEcoNet) in the Yellow River Basin in which forest patches are represented as nodes (sources) and their interactions as edges (corridors). Our objective was to optimize the ForEcoNet’s structure and enhance forest carbon stocks. First, we employed downscaling technology to allocate the forest carbon stocks of the 69 cities in the study area to grid cells, generating a spatial distribution map of forest carbon density in the Yellow River Basin. Next, we conducted morphological spatial pattern analysis (MSPA) and used the minimum cumulative resistance model (MCR) to extract the ForEcoNet in the basin. Finally, we proposed optimization of the ForEcoNet based on the coupling coordination between the node carbon stock and topological structure. The results showed that: (1) the forest carbon stocks of the upper, middle, and lower reaches accounted for 42.35%, 54.28%, and 3.37% of the total, respectively, (2) the ForEcoNet exhibited characteristics of both a random network and a scale-free network and demonstrated poor network stability, and (3) through the introduction of 51 sources and 46 corridors, we optimized the network and significantly improved its robustness. These findings provide scientific recommendations for the optimization of forest allocation in the Yellow River Basin and achieving the goal of increasing the forest carbon stock.

Gemcitabine (GEM) is the gold-standard therapeutic regimen for patients with pancreatic cancer (PC); however, patients may receive limited benefits due to the drug resistance of GEM. LncRNA SNHG6 is reported to play key roles in drug resistance, but its role and molecular mechanism in PC remain incompletely understood. We found that LncRNA SNHG6 is drastically downregulated in GEM-resistant PC and is positively correlated with the survival of PC patients. With the help of bioinformatic analysis and molecular approaches, we show that LncRNA SNHG6 can sponge miR-944, therefore causing the upregulation of the target gene KPNA5. In vitro experiments showed that LncRNA SNHG6 and KPNA5 suppress PC cell proliferation and colony formation. The Upregulation of LncRNA SNHG6 and KPNA5 increases the response of GEM-resistant PANC-1 cells to GEM. We also show that the expression of KPNA5 is higher in patients without GEM resistance than in those who developed GEM resistance. In summary, our findings indicate that the LncRNA SNHG6/miR944/KPNA5 axis plays a pivotal role in overcoming GEM resistance, and targeting this axis may contribute to an increasing of the benefits of PC patients from GEM treatment.

Chenodeoxycholic acid (CDCA), a primary bile acid (BA), has been demonstrated to play an important role as a signaling molecule in various physiological functions. However, the role of CDCA in regulating intestinal epithelial cell (IEC) function remains largely unknown. Herein, porcine intestinal epithelial cells (IPEC-J2) were used as an in vitro model to investigate the effects of CDCA on IEC proliferation and explore the underlying mechanisms. IPEC-J2 cells were treated with CDCA, and flow cytometry and transcriptome analysis were adopted to investigate the effects and potential molecular mechanisms of CDCA on the proliferation of IECs. Our results indicated that adding 50 μmol/L of CDCA in the media significantly increased the proliferation of IPEC-J2 cells. In addition, CDCA treatment also hindered cell apoptosis, increased the proportion of G0/G1 phase cells in the cell cycle progression, reduced intracellular ROS, and MDA levels, and increased mitochondrial membrane potential, antioxidation enzyme activity (T-AOC and CAT), and intracellular ATP level (p < 0.05). RNA-seq results showed that CDCA significantly upregulated the expression of genes related to cell cycle progression (Cyclin-dependent kinase 1 (CDK1), cyclin G2 (CCNG2), cell-cycle progression gene 1 (CCPG1), Bcl-2 interacting protein 5 (BNIP5), etc.) and downregulated the expression of genes related to mitochondrial biogenesis (ND1, ND2, COX3, ATP6, etc.). Further KEGG pathway enrichment analysis showed that CDCA significantly enriched the signaling pathways of DNA replication, cell cycle, and p53. Collectively, this study demonstrated that CDCA could promote IPEC-J2 proliferation by regulating cell cycle progression and mitochondrial function. These findings provide a new strategy for promoting the intestinal health of pigs by regulating intestinal BA metabolism.

Rice (Oryza sativa) OsMADS58 is a C-class MADS box protein, and characterization of a transposon insertion mutant osmads58 suggested that OsMADS58 plays a role in stamen development. However, as no null mutation has been obtained, its role has remained unclear. Here, we report that the CRISPR knockout mutant osmads58 exhibits complex altered phenotypes, including anomalous diploid germ cells, aberrant meiosis, and delayed tapetum degeneration. This CRISPR mutant line exhibited stronger changes in expression of OsMADS58 target genes compared with the osmads58 dSpm (transposon insertion) line, along with changes in multiple pathways related to early stamen development. Notably, transcriptional regulatory circuits in young panicles covering the stamen at stages 4–6 were substantially altered in the CRISPR line compared to the dSpm line. These findings strongly suggest that the pleiotropic effects of OsMADS58 on stamen development derive from a potential role in stabilizing gene regulatory circuits during early stamen development. Thus, this work opens new avenues for viewing and deciphering the regulatory mechanisms of early stamen development from a network perspective.

Wind and rainfall climatic erosivities are important parameters with which to assess the possible effects of climatic conditions on erosion. In this study, wind erosion climatic erosivity (C-factor) and rainfall erosivity (Rday-factor) were calculated for the period 1970–2020 based on data from 50 meteorological stations in Qinghai Province. The Mann–Kendall test, trend analysis, and K-means clustering method were used to explore the spatiotemporal characteristics of regional wind/rainfall climatic erosivity. Results showed that the annual mean value of the C-factor was 25.8 over the past 51 years, with an obvious trend of decline of 6.5/10a. The mean annual value of the Rday-factor was 491.6 MJ·mm/(hm2·h·a), with an obvious trend of increasing of 24.0 MJ·mm/(hm2·h·10a). Strong seasonality was found in both the C-factor and the Rday-factor. The highest values of the C-factor were found in late winter and spring, accounting for a substantial proportion of the annual C-factor (48.6%). Rainfall erosivity occurred mainly April–October, with the highest values in summer, accounting for a substantial proportion of the annual Rday-factor (72.9%). Wind-erosion climatic erosivity and rainfall erosivity were obviously asynchronous on an annual basis, and the period of their combination extended the time of soil erosion. Through k-means clustering analysis, climatic erosivity in Qinghai Province was divided into three regions: the first dominated by wind-erosion climatic erosivity, the second dominated by rainfall erosivity, and the third dominated by their combination. The most serious land erosion occurred in the third region, accounting for 34.3% of the entire land area of Qinghai Province, where annual rainfall was found to be broadly consistent at 300–400 mm. Wind speed, temperature, rainfall, and sunshine duration are key factors known to impact the variation in wind-erosion climatic erosivity, while annual erosive rainfall, number of rainy days, and sunshine duration are the main factors known to impact the variation in rainfall erosivity. The findings of this study represent a robust reference for ecoenvironmental protection, sustainable development, and soil protection.

The objective of the present work is to evaluate the influence of material color on mechanical properties of fused deposition modeling (FDM) parts. The performance of the products is evaluated by testing eight different colors of acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) material in terms of tensile strength, compressive strength, and flexural strength. The analysis of data shows a significant difference in mechanical characteristics of prints depending on filament color. For different colors, these three strengths almost follow the same rising and falling tendency. In order to explore the relationship between mechanical strengths and filament colors, the color-mixing theory and the least-squares method are adopted to fit the best ratio coefficients of different color combinations. Results are presented showing that the strength value (e.g., tensile) of the mixed color can be evaluated through that of primary colors by fitting the other strength (e.g., compressive or flexural). It is shown that the predicted value is always no more than 7% error compared with the actual strength, in spite of two-color or three-color mixtures. An additional confirmation test with seven colored PLA filaments from different suppliers was conducted to focus on the extensibility. The outcomes show the maximum fitting errors of strengths for mixed colors in all cases are within 5%, proving the effectiveness and applicability of this predicted approach. This study can bring a detailed analysis that enables better estimation of the function of material color and contributes to improving the property of FDM printed products for consumers by choosing the suitable filament color.

In recent years, much research has been conducted on time series based human activity recognition (HAR) using wearable sensors. Most existing work for HAR is based on the manual labeling. However, the complete time serial signals not only contain different types of activities, but also include many transition and atypical ones. Thus, effectively filtering out these activities has become a significant problem. In this paper, a novel machine learning based segmentation scheme with a multi-probability threshold is proposed for HAR. Threshold segmentation (TS) and slope-area (SA) approaches are employed according to the characteristics of small fluctuation of static activity signals and typical peaks and troughs of periodic-like ones. In addition, a multi-label weighted probability (MLWP) model is proposed to estimate the probability of each activity. The HAR error can be significantly decreased, as the proposed model can solve the problem that the fixed window usually contains multiple kinds of activities, while the unknown activities can be accurately rejected to reduce their impacts. Compared with other existing schemes, computer simulation reveals that the proposed model maintains high performance using the UCI and PAMAP2 datasets. The average HAR accuracies are able to reach 97.71% and 95.93%, respectively.

In the present study, a comparison of two widely used optimization approaches for fused deposition modeling (FDM), that is, Taguchi method in contrast with response surface method (RSM), was investigated. Four operating parameters, namely extrusion temperature, layer thickness, raster width, print speed, and their interaction terms, were identified as control variables with three levels, while tensile strength and compressive strength were selected responses. L27 orthogonal array and face-centered central composite design (FCCCD) were used for the experimental approach for Taguchi and RSM, respectively. The signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were employed to find the optimal FDM parameter combination as well as the main factor that affect the performance of the PLA samples. Based on experimental results, it was observed that conclusions about significant ranking of parameters on FDM process from these two methods were different. However, both the Taguchi method and RSM succeed in predicting better results compared with the original groups. In addition, the optimum combinations for tensile strength and compressive strength obtained from the RSM were 2.11% and 8.15% higher than Taguchi method, respectively.

Ripened oriental melon (Cucumis melo) with orange-colored flesh is rich in β-carotene. Lycopene β-cyclase (LCYB) is the synthetic enzyme that directly controls the massive accumulation of β-carotene. However, the regulatory mechanism underlying the CmLCYB-mediated β-carotene accumulation in oriental melon is fairly unknown. Here, we screened and identified a transcription factor, CmNAC34, by combining bioinformatics analysis and yeast one-hybrid screen with CmLCYB promoter. CmNAC34 was located in the nucleus and acted as a transcriptional activator. The expression profile of CmNAC34 was consistent with that of CmLCYB during the fruit ripening. Additionally, the transient overexpression of CmNAC34 in oriental melon fruit promoted the expression of CmLCYB and enhanced β-carotene concentration, while transient silence of CmNAC34 in fruit was an opposite trend, which indicated CmNAC34 could modulate CmLCYB-mediated β-carotene biosynthesis in oriental melon. Finally, the yeast one-hybrid (Y1H), electrophoretic mobility shift assay (EMSA), β-glucuronidase (GUS) analysis assay, and luciferase reporter (LUC) assay indicated that CmNAC34 could bind to the promoter of CmLCYB and positively regulated the CmLCYB transcription level. These findings suggested that CmNAC34 acted as an activator to regulate β-carotene accumulation by directly binding the promoter of CmLCYB, which provides new insight into the regulatory mechanism of carotenoid metabolism during the development and ripening of oriental melon.

Due to the availability of materials and low cost for production, fused deposition modeling is becoming the most widely used additive manufacturing (AM) technology. However, the reasonable choice of process parameters for FDM is a significant task that directly affects the performance of the printed part. Therefore, it is necessary to investigate the influences of various process parameters on the quality characteristics of the components. The objectives of this study are to thoroughly review the current state of research that characterizes, estimates the effects of process parameters on mechanical properties, and summarizes the conclusions of existing works. In addition, some general issues of the presented research are summarized, and the need for future development is also emphasized. Finally, the research proposes several areas that deserve further study in this field.

Photocrosslinked Gelatin–Methacryloyl (GelMA) has been widely used in the field of 3D bioprinting due to its excellent biological properties, but its properties are not yet optimized. With the advent of embedded printing, the balance between hydrogel printability and cell viability is expected to be achieved. Agarose microgel is a good support material because of its simple preparation, good biocompatibility, high melting point, and good rheology. In this study, aiming at realizing a GelMA/Agarose suspension printing system, the printing effect of the suspension process was explored, and a suitable process printing window was defined. The resulting scaffolds showed better water absorption and elasticity, but larger deformation during printing. This study explored some potential roles of suspension baths in embedded printing, paving the way for the preparation of good suspension structures that can be convenient for customized tissue engineering applications.

Precise classification of bacteria facilitates prediction of their ecological niche. The genus Enterobacter includes pathogens of plants and animals but also beneficial bacteria that may require reclassification. Here, we propose reclassification of Enterobacter FY-07 (FY-07), a strain that has many plant-growth-promoting traits and produces bacterial cellulose (BC), to the Kosakonia genera. To re-examine the taxonomic position of FY-07, a polyphasic approach including 16S rRNA gene sequence analysis, ATP synthase β subunit (atpD) gene sequence analysis, DNA gyrase (gyrB) gene sequence analysis, initiation translation factor 2 (infB) gene sequence analysis, RNA polymerase β subunit (rpoB) gene sequence analysis, determination of DNA G + C content, average nucleotide identity based on BLAST, in silico DNA–DNA hybridization and analysis of phenotypic features was applied. This polyphasic analysis suggested that Enterobacter sp. FY-07 should be reclassified as Kosakonia oryzendophytica FY-07. In addition, the potential of FY-07 to promote plant growth was also investigated by detecting related traits and the colonization of FY-07 in rice roots.

As the leading causes of global death, cardiovascular diseases are generally initiated by artery-related disorders such as atherosclerosis, thrombosis, and aneurysm. Although clinical treatments have been developed to rescue patients suffering from artery-related disorders, the underlying pathologies of these arterial abnormalities are not fully understood. Biofabrication techniques pave the way to constructing diseased artery in vitro models using human vascular cells, biomaterials, and biomolecules, which are capable of recapitulating arterial pathophysiology with superior performance compared with conventional planar cell culture and experimental animal models. This review discusses the critical elements in the arterial microenvironment which are important considerations for recreating biomimetic human arteries with the desired disorders in vitro. Afterward, conventionally biofabricated platforms for the investigation of arterial diseases are summarized, along with their merits and shortcomings, followed by a comprehensive review of advanced biofabrication techniques and the progress of their applications in establishing diseased artery models.

Zebrafish are widely used to investigate candidate genes for human diseases. While the emergence of CRISPR-Cas9 technology has revolutionized gene editing, the use of individual guide RNAs limits the efficiency and application of this technology in functional genetics research. Multiplexed genome editing significantly enhances the efficiency and scope of gene editing. Herein, we describe an efficient multiplexed genome editing strategy to generate zebrafish mutants. Following behavioural tests and histological examination, we identified one new candidate gene (tmem183a) for hearing loss. This study provides a robust genetic platform to quickly obtain zebrafish mutants and to identify candidate genes by phenotypic readouts.

Induced pluripotent stem cells (iPSCs) are essentially produced by the genetic reprogramming of adult cells. Moreover, iPSC technology prevents the genetic manipulation of embryos. Hence, with the ensured element of safety, they rarely cause ethical concerns when utilized in tissue engineering. Several cumulative outcomes have demonstrated the functional superiority and potency of iPSCs in advanced regenerative medicine. Recently, an emerging trend in 3D bioprinting technology has been a more comprehensive approach to iPSC-based tissue engineering. The principal aim of this review is to provide an understanding of the applications of 3D bioprinting in iPSC-based tissue engineering. This review discusses the generation of iPSCs based on their distinct purpose, divided into two categories: (1) undifferentiated iPSCs applied with 3D bioprinting; (2) differentiated iPSCs applied with 3D bioprinting. Their significant potential is analyzed. Lastly, various applications for engineering tissues and organs have been introduced and discussed in detail.

Alginate is a natural polysaccharide that typically originates from various species of algae. Due to its low cost, good biocompatibility, and rapid ionic gelation, the alginate hydrogel has become a good option of bioink source for 3D bioprinting. However, the lack of cell adhesive moieties, erratic biodegradability, and poor printability are the critical limitations of alginate hydrogel bioink. This review discusses the pivotal properties of alginate hydrogel as a bioink for 3D bioprinting technologies. Afterward, a variety of advanced material formulations and biofabrication strategies that have recently been developed to overcome the drawbacks of alginate hydrogel bioink will be focused on. In addition, the applications of these advanced solutions for 3D bioprinting of tissue/organ mimicries such as regenerative implants and in vitro tissue models using alginate-based bioink will be systematically summarized.

This study evaluated the effects of dietary gallic acid (GA) on growth performance, diarrhea incidence and plasma antioxidant status of weaned piglets regardless of whether weaning weight was high or low. A total of 120 weaned piglets were randomly allocated to four treatments in a 42-day experiment with a 2 × 2 factorial treatment arrangement comparing different weaning weights (high weight (HW) or low weight (LW), 8.49 ± 0.18 kg vs. 5.45 ± 0.13 kg) and dietary treatment (without supplementation (CT) or with supplementation of 400 mg/kg of GA). The results showed that HW piglets exhibited better growth performance and plasma antioxidant capacity. Piglets supplemented with GA had higher body weight (BW) on day 42 and average daily gain (ADG) from day 0 to 42 compared to the control piglets, which is mainly attributed to the specific improvement on BW and ADG of LW piglets by the supplementation of GA. The decreased values of diarrhea incidence were seen in piglets fed GA, more particularly in LW piglets. In addition, dietary GA numerically reduced malondialdehyde (MDA) content in plasma of LW piglets. In conclusion, our study suggests that dietary GA may especially improve the growth and health in LW weaned piglets.

In China, SMEs are facing financing difficulties, and commercial banks and financial institutions are the main financing channels for SMEs. Thus, a reasonable and efficient credit risk assessment system is important for credit markets. Based on traditional statistical methods and AI technology, a soft voting fusion model, which incorporates logistic regression, support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), is constructed to improve the predictive accuracy of SMEs’ credit risk. To verify the feasibility and effectiveness of the proposed model, we use data from 123 SMEs nationwide that worked with a Chinese bank from 2016 to 2020, including financial information and default records. The results show that the accuracy of the soft voting fusion model is higher than that of a single machine learning (ML) algorithm, which provides a theoretical basis for the government to control credit risk in the future and offers important references for banks to make credit decisions.

Fiscal sustainability is an issue of great concern for governments globally and air pollution control has become an important factor affecting fiscal sustainability. This study aims to examine the impact of air pollution on fiscal sustainability in the short and long run. We conducted an empirical analysis based on air pollution and local government debt data on China’s prefecture-level cities in 2014–2019, using regression discontinuity design (RDD) and a panel data model. The results show that air pollution reduces the debt burden of governments in the short run. However, in the long run, addressing the negative impacts of air pollution adds to the debt burden of local governments, hindering fiscal sustainability. Fiscal freedom and the level of public services significantly moderate the negative impact of air pollution on fiscal sustainability. A higher level of fiscal freedom generally indicates a greater incentive for local governments to raise pollutant emission standards, strengthen the construction of green infrastructure, and subsidize green enterprises. Furthermore, a higher level of public services reflects better infrastructure and higher levels of investment in environmental protection, which help to reduce the negative impact of air pollution. The governments are suggested to take measures to effectively control air pollution, so as to enhance fiscal stability in the long run.

With the rapid development of the computer and sensor field, inertial sensor data have been widely used in human activity recognition. At present, most relevant studies divide human activities into basic actions and transitional actions, in which basic actions are classified by unified features, while transitional actions usually use context information to determine the category. For the existing single method that cannot well realize human activity recognition, this paper proposes a human activity classification and recognition model based on smartphone inertial sensor data. The model fully considers the feature differences of different properties of actions, uses a fixed sliding window to segment the human activity data of inertial sensors with different attributes and, finally, extracts the features and recognizes them on different classifiers. The experimental results show that dynamic and transitional actions could obtain the best recognition performance on support vector machines, while static actions could obtain better classification effects on ensemble classifiers; as for feature selection, the frequency-domain feature used in dynamic action had a high recognition rate, up to 99.35%. When time-domain features were used for static and transitional actions, higher recognition rates were obtained, 98.40% and 91.98%, respectively.

Advances in three-dimensional (3D) printing techniques and the development of tailored biomaterials have facilitated the precise fabrication of biological components and complex 3D geometrics over the past few decades. Moreover, the notable growth of 3D printing has facilitated pharmaceutical applications, enabling the development of customized drug screening and drug delivery systems for individual patients, breaking away from conventional approaches that primarily rely on transgenic animal experiments and mass production. This review provides an extensive overview of 3D printing research applied to drug screening and drug delivery systems that represent pharmaceutical applications. We classify several elements required by each application for advanced pharmaceutical techniques and briefly describe state-of-the-art 3D printing technology consisting of cells, bioinks, and printing strategies that satisfy requirements. Furthermore, we discuss the limitations of traditional approaches by providing concrete examples of drug screening (organoid, organ-on-a-chip, and tissue/organ equivalent) and drug delivery systems (oral/vaginal/rectal and transdermal/surgical drug delivery), followed by the introduction of recent pharmaceutical investigations using 3D printing-based strategies to overcome these challenges.

The musculoskeletal system is a vital body system that protects internal organs, supports locomotion, and maintains homeostatic function. Unfortunately, musculoskeletal disorders are the leading cause of disability worldwide. Although implant surgeries using autografts, allografts, and xenografts have been conducted, several adverse effects, including donor site morbidity and immunoreaction, exist. To overcome these limitations, various biomedical engineering approaches have been proposed based on an understanding of the complexity of human musculoskeletal tissue. In this review, the leading edge of musculoskeletal tissue engineering using 3D bioprinting technology and musculoskeletal tissue-derived decellularized extracellular matrix bioink is described. In particular, studies on in vivo regeneration and in vitro modeling of musculoskeletal tissue have been focused on. Lastly, the current breakthroughs, limitations, and future perspectives are described.

Three-dimensional (3D) point cloud registration is an important step in three-dimensional (3D) model reconstruction or 3D mapping. Currently, there are many methods for point cloud registration, but these methods are not able to simultaneously solve the problem of both efficiency and precision. We propose a fast method of global registration, which is based on RGB (Red, Green, Blue) value by using the four initial point pairs (FIPP) algorithm. First, the number of different RGB values of points in a dataset are counted and the colors in the target dataset having too few points are discarded by using a color filter. A candidate point set in the source dataset are then generated by comparing the similarity of colors between two datasets with color tolerance, and four point pairs are searched from the two datasets by using an improved FIPP algorithm. Finally, a rigid transformation matrix of global registration is calculated with total least square (TLS) and local registration with the iterative closest point (ICP) algorithm. The proposed method (RGB-FIPP) has been validated with two types of data, and the results show that it can effectively improve the speed of 3D point cloud registration while maintaining high accuracy. The method is suitable for points with RGB values.

DNA viruses are known to be associated with a variety of different cancers. Human papillomaviruses (HPV) are a family of viruses and several of its sub-types are classified as high-risk HPVs as they are found to be associated with the development of a number of different cancers. Almost all cervical cancers appear to be driven by HPV infection and HPV is also found in most cancers of the anus and at least half the cancers of the vulva, penis and vagina, and increasingly found in one sub-type of head and neck cancers namely oropharyngeal squamous cell carcinoma. Our understanding of HPVs role in cancer development comes from extensive studies done on cervical cancer and it has just been assumed that HPV plays an identical role in the development of all other cancers arising in the presence of HPV sequences, although this has not been proven. Most invasive cervical cancers have the HPV genome integrated into one or more sites within the human genome. One powerful tool to examine all the sites of HPV integration in a cancer but that also provides a comprehensive view of genomic alterations in that cancer is the use of next generation sequencing of mate-pair libraries produced from the DNA isolated. We will describe how this powerful technology can provide important information about the genomic organization within an individual cancer genome, and how this has demonstrated that HPVs role in oropharyngeal squamous cell carcinoma is distinct from that in cervical cancer. We will also describe why the sequencing of mate-pair libraries could be a powerful clinical tool for the management of patients with a DNA viral etiology and how this could quickly transform the care of these patients.

Coreness is one of the important indicators to measure the importance of a node. Traditionally, the coreness of a node is measured by k-core decomposition. However, to measure the coreness in a dynamic network, the k-core decomposition method becomes very time-consuming and inefficient, and cannot meet the need in very large real networks. Recently, the H operator method was proposed to calculate the coreness of a node, which provides a novel method to deal with the coreness of a node in a network. In this paper, we decode the coreness variation rule by a symmetric pair of experiments, i.e., deleting and adding edge, on real networks. Then, an algorithm to fast update the coreness of related nodes is proposed. Results on five real networks showed that the performance of the proposed algorithm was greatly enhanced and comprehensively superior to the k-core decomposition algorithm. Our study provides a promising way to optimize the algorithm of coreness calculation in the dynamic networks.

Constructing elaborate catalysts to prompt the charge carrier separation and transport is critical to developing efficient photocatalytic systems. Here, a hierarchical hollow structure based on 1D/2D BiOCl/Bi2WO6 hybrid materials was fabricated by a precursor chemical engineering method. This hybrid is made up of molten 1D BiOCl nanorods and 2D Bi2WO6 nanosheets. The synergetic effect of the presence of BiOCl and specific interfaces between BiOCl and Bi2WO6 provided efficient interfacial charge transfer of photogenerated carriers under visible light. Seamless BiOCl functions like a noble metal, with platinum-like behavior, accelerating the oxidizing ability of fabricated BiOCl/Bi2WO6 hybrids, which was favorable for the photocatalytic decomposition of organic compounds (3.2 times greater for Rhodamine B (RhB) and 4 times greater for Ciprofloxacin (CIP)) over the Bi2WO6 catalysts. The beneficial interfacial interaction between BiOCl and Bi2WO6 resulting from the unique construction prompted the charge transfer from the conduction band of Bi2WO6 to that of BiOCl. The findings presented in this study provide a cost-effective precursor-mediated strategy to realize the critical and efficient separation of photoinduced carriers in environmental remediation applications.

In addition to the acute manifestations of respiratory syncytial virus (RSV), persistent infection may be associated with long-term complications in the development of chronic respiratory diseases. To understand the mechanisms underlying RSV-induced long-term consequences, we established an in vitro RSV (strain A2) infection model using human bronchial epithelial (16HBE) cells that persists over four generations and analyzed cell inflammation and matrix adherence. Cells infected with RSV at multiplicity of infection (MOI) 0.0067 experienced cytolytic or abortive infections in the second generation (G2) or G3 but mostly survived up to G4. Cell morphology, leukocyte and matrix adherence of the cells did not change in G1 or G2, but subsequently, leukocyte adherence and cytokine/chemokine secretion, partially mediated by intercellular adhesion molecule-1 (ICAM-1), increased drastically, and matrix adherence, partially mediated by E-cadherin, decreased until the cells died. Tumor necrosis factor-α (TNF-α) secretion was inhibited by ICAM-1 antibody in infected-16HBE cells, suggesting that positive feedback between TNF-α secretion and ICAM-1 expression may be significant in exacerbated inflammation. These data demonstrate the susceptibility of 16HBE cells to RSV and their capacity to produce long-term progressive RSV infection, which may contribute to inflammation mobilization and epithelial shedding.

Novel magnetic-antimicrobial-fluorescent multifunctional hybrid microspheres with well-defined nanostructure were synthesized by the aid of a poly(glycidyl methacrylate) (PGMA) template. The hybrid microspheres were fully characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared (FTIR), X-ray diffraction (XRD) and digital fluorescence microscope. The as-synthesized microspheres PGMA, amino-modified PGMA (NH2-PGMA) and magnetic PGMA (M-PGMA) have a spherical shape with a smooth surface and fine monodispersity. M-PGMA microspheres are super-paramagnetic, and their saturated magnetic field is 4.608 emu·g−1, which made M-PGMA efficiently separable from aqueous solution by an external magnetic field. After poly(haxemethylene guanidine hydrochloride) (PHGH) functionalization, the resultant microspheres exhibit excellent antibacterial performance against both Gram-positive and Gram-negative bacteria. The fluorescence feature originating from the quantum dot CdTe endowed the hybrid microspheres with biological functions, such as targeted localization and biological monitoring functions. Combination of magnetism, antibiosis and fluorescence into one single hybrid microsphere opens up the possibility of the extensive study of multifunctional materials and widens the potential applications.

Selective catalytic reduction (SCR) with NH3 is the most efficient and economic flue gas denitrification technology developed to date. Due to its high low-temperature catalytic activity, Mn-based catalysts present a great prospect for application in SCR de-NOx at low temperatures. However, overcoming the poor resistance of Mn-based catalysts to H2O and SO2 poison is still a challenge. This paper reviews the recent progress on the H2O and SO2 resistance of Mn-based catalysts for the low-temperature SCR of NOx. Firstly, the poison mechanisms of H2O and SO2 are introduced in detail, respectively. Secondly, Mn-based catalysts are divided into three categories—single MnOx catalysts, Mn-based multi-metal oxide catalysts, and Mn-based supported catalysts—to review the research progress of Mn-based catalysts for H2O and SO2 resistance. Thirdly, several strategies to reduce the poisonous effects of H2O and SO2, such as metal modification, proper support, the combination of metal modification and support, the rational design of structure and morphology, are summarized. Finally, perspectives and future directions of Mn-based catalysts for the low-temperature SCR of NOx are proposed.

In response to the wide spread of microbial contamination induced by bacterial pathogens, the development of novel materials with excellent antibacterial activity is of great interest. In this study, novel antibacterial chitosan (CS) and polyhexamethylene guanidine hydrochloride (PHGC) dual-polymer-functionalized graphene oxide (GO) (GO-CS-PHGC) composites were designed and easily fabricated. The as-prepared materials were characterized by Fourier transform infrared (FTIR), X-ray photoelectron spectrometer (XPS), field emission scanning electron microscopy (FE-SEM), transmission electron microscope (TEM), thermogravimetric analysis (TGA) and Raman spectroscopy. Their antibacterial capability towards bacterial strains was also studied by incubating both Gram-negative bacteria and Gram-positive bacteria in their presence. More significantly, the synergistic antibacterial action of the three components was assayed, and the findings implied that the as-prepared GO-CS-PHGC shows enhanced antibacterial activity when compared to its single components (GO, CS, PHGC or CS-PHGC) and the mixture of individual components. Not only Gram-negative bacteria but also Gram-positive bacteria are greatly inhibited by GO-CS-PHGC composites. The minimum inhibitory concentration (MIC) value of GO-CS-PHGC against E. coli was 32 μg/mL. With the powerful antibacterial activity as well as its low cost and facile preparation, GO-CS-PHGC has potential applications as a novel antibacterial agent in a wide range of biomedical uses.