Mesenchymal stem cells (MSCs) are promising seed cells for neural regeneration therapy owing to their plasticity and accessibility. They possess several inherent characteristics advantageous for the transplantation-based treatment of neurological disorders, including neural differentiation, immunosuppression, neurotrophy, and safety. However, the therapeutic efficacy of MSCs alone remains unsatisfactory in most cases. To improve some of their abilities, many studies have employed genetic engineering to transfer key genes into MSCs. Both viral and nonviral methods can be used to overexpress therapeutic proteins that complement the inherent properties. However, to date, different modes of gene transfer have specific drawbacks and advantages. In addition, MSCs can be functionalized through targeted gene modification to facilitate neural repair by promoting neural differentiation, enhancing neurotrophic and neuroprotective functions, and increasing survival and homing abilities. The methods of gene transfer and selection of delivered genes still need to be optimized for improved therapeutic and targeting efficacies while minimizing the loss of MSC function. In this review, we focus on gene transport technologies for engineering MSCs and the application of strategies for selecting optimal delivery genes. Further, we describe the prospects and challenges of their application in animal models of different neurological lesions to broaden treatment alternatives for neurological diseases.
Spinal cord injury (SCI) is a serious clinical disease. Due to the deformability and fragility of the spinal cord, overly rigid hydrogels cannot be used to treat SCI. Hence, we used TPA and Laponite to develop a hydrogel with shear-thinning ability. This hydrogel exhibits good deformation, allowing it to match the physical properties of the spinal cord; additionally, this hydrogel scavenges ROS well, allowing it to inhibit the lipid peroxidation caused by ferroptosis. According to the in vivo studies, the TPA@Laponite hydrogel could synergistically inhibit ferroptosis by improving vascular function and regulating iron metabolism. In addition, dental pulp stem cells (DPSCs) were introduced into the TPA@Laponite hydrogel to regulate the ratios of excitatory and inhibitory synapses. It was shown that this combination biomaterial effectively reduced muscle spasms and promoted recovery from SCI.
The COVID-19 pandemic remains ever prevalent and afflicting—partially because one of its transmission pathways is aerosol. With the widely used central air conditioning systems worldwide, indoor virus aerosols can rapidly migrate, thus resulting in rapid infection transmission. It is therefore important to install microbial aerosol treatment units in the air conditioning systems, and we herein investigated the possibility of combining such filtration with UV irradiation to address virus aerosols. Results showed that the removal efficiency of filtration towards f2 and MS2 phages depended on the type of commercial filter material and the filtration speed, with an optimal velocity of 5 cm/s for virus removal. Additionally, it was found that UV irradiation had a significant effect on inactivating viruses enriched on the surfaces of filter materials; MS2 phages had greater resistance to UV-C irradiation than f2 phages. The optimal inactivation time for UV-C irradiation was 30 min, with higher irradiation times presenting no substantial increase in inactivation rate. Moreover, excessive virus enrichment on the filters decreased the inactivation effect. Timely inactivation is therefore recommended. In general, the combined system involving filtration with UV-C irradiation demonstrated a significant removal effect on virus aerosols. Moreover, the system is simple and economical, making it convenient for widespread implementation in air-conditioning systems.
The increasing interest around emotions in online texts creates the demand for financial sentiment analysis. Previous studies mainly focus on coarse-grained document-/sentence-level sentiment analysis, which ignores different sentiment polarities of various targets (e.g., company entities) in a sentence. To fill the gap, from a fine-grained target-level perspective, we propose a novel Lexicon Enhanced Collaborative Network (LECN) for targeted sentiment analysis (TSA) in financial texts. In general, the model designs a unified and collaborative framework that can capture the associations of targets and sentiment cues to enhance the overall performance of TSA. Moreover, the model dynamically incorporates sentiment lexicons to guide the sentiment classification, which cultivates the model faculty of understanding financial expressions. In addition, the model introduces a message selective-passing mechanism to adaptively control the information flow between two tasks, thereby improving the collaborative effects. To verify the effectiveness of LECN, we conduct experiments on four financial datasets, including SemEVAL2017 Task5 subset1, SemEVAL2017 Task5 subset2, FiQA 2018 Task1, and Financial PhraseBank. Results show that LECN achieves improvements over the state-of-art baseline by 1.66 p.p., 1.47 p.p., 1.94 p.p., and 1.88 p.p. in terms of F1-score. A series of further analyses also indicate that LECN has a better capacity for comprehending domain-specific expressions and can achieve the mutually beneficial effect between tasks.
Cellular automata (CA) has become one of the most prevalent approaches for spatially explicit urban growth modeling. Previous studies have investigated how the key components of CA models are defined, structured, and coupled to represent the top-down and bottom-up processes of urban growth. However, the spatiotemporal heterogeneity of urban demand at the macro level and its coupling with micro-level urban land configurations have not been fully explored in existing CA models. This study proposes a new urban CA modeling framework to simulate urban expansion by using a spatiotemporally explicit urban demand modeling scheme that guides the patch-based allocation of urban land at the micro level. In this framework, spatiotemporal Gaussian-based models were applied to represent the spatiotemporal heterogeneity of urban demand within a set of concentric rings in terms of the fraction of new urban land and frequency of new urban development. An application of the modeling framework to the metropolitan city of Wuhan, China demonstrates that the demand of new urban land in the study area exhibits an outgoing wave-shaped propagation pattern, which can be well fitted by the spatiotemporal Gaussian-based models, with R² values exceeding 0.8. The proposed spatiotemporally explicit representation of urban demand can improve model performance in capturing urban dynamics at both macro and micro levels, as revealed by pattern-level similarity and cell-level agreement of simulation results.
Previous literature gave considerable attention to antecedents of health-risk information seeking, but few elaborated on its cognitive and affective outcomes, and how individual differences may influence this link. Based on a survey (N = 1743) conducted during the COVID-19 pandemic, we seek to interpret the influence of health-risk information seeking on media trust and emotions, and how methods of information processing moderate this link. Results demonstrated that COVID-19-related information seeking from the media decreased the belief that media distort reality, which in turn decreased fear; and increased the belief that media provide validity cues, which further increased calmness. The negative relationship between information seeking and the belief that media distort reality was stronger when heuristic processing was high, while the positive association between information seeking and the belief that media provide validity cues was strong only when systematic processing was low. Results contributed to information seeking studies by identifying the cognitive and affective outcomes of information seeking, and also lent insights to health-risk communication studies by showing how information seeking would increase media trust and positive emotions, and the moderating effect of information processing methods on media effects.
Drawing on self-representation theory, we explore how trait competitiveness affects innovative behavior and career satisfaction via perceived insider status and the boundary role of perceived leader competitiveness. Data were collected in two waves among 316 employees in China. The results showed that employee trait competitiveness was positively related to innovative behavior and career satisfaction via perceived insider status. These indirect effects were significantly stronger when working with competitive leaders and were insignificant otherwise. Our findings make theoretical contributions and practical implications regarding how, and under what circumstances, competitive employees will innovate and satisfy with their career development.
Under intense fiscal pressure, China's local governments raced against each other to offer business-friendly policies to mobile industries. Lax environmental enforcement was widely adopted across the country and many poor regions became havens for polluting factories. We argue that this adverse effect went deeper than the interjurisdictional competition argument. Within each jurisdiction, urban and rural communities engaged in a similar rivalry. Local governments, facing stronger societal environmental pressure from urban communities, prioritized urban environment and allocated fewer administrative resources to rural environment enforcement. As a result, polluting enterprises found refuge in the rural part of these jurisdictions. We merge a national firm registry database with a national survey of polluting enterprises firms and find strong evidence supporting this hypothesis. Our research extends the scope of the pollution haven hypothesis from an inter-jurisdictional dimension to the urban-rural divide, a source of environmental injustice that is understudied in the literature. Our study of firm location choices also complements current researches on Chinese rural pollution by highlighting the political and economic causes of pollution.
Background Hypoxia is an important microenvironmental factor that induces Endometriosis (EMs), but its mechanism remains unclear. Our study aims to investigate the mechanisms of miR-150-5p on hypoxia-induced EMs. Methods Ovarian endometriosis cyst wall stromal cell lines CRL-7566 cells were treated with hypoxia. Cell migration ability was measured by Transwell assay. qRT-PCR was performed to detect miR-150-5p and PDCD4 expression. The autophagy-related proteins (LC3-I, LC3-II, Beclin-1, and p62), epithelial-mesenchymal transition (EMT) related proteins (E-cadherin, N-cadherin, and Vimentin) and NF-κB signaling pathway related proteins p65 expression were measured by western blot. Dual-luciferase reporter gene assay verified the binding relationship between miR-150-5p and PDCD4. Results After hypoxia treatment, the miR-150-5p expression was up-regulated in CRL-7566 cells, while the expression of PDCD4 was down-regulated. In CRL-7566 cells, autophagy, migration and EMT were increased after hypoxia treatment. The autophagy inhibitor 3-MA inhibited hypoxia-induced the autophagy, migration and EMT of CRL-7566 cells. Hypoxia-induced autophagy and EMT of CRL-7566 cells were inhibited after knocking down miR-150-5p. Then miR-150-5p negatively regulated PDCD4 expression. PDCD4 knockdown reversed the inhibitory effect of miR-150-5p silencing on hypoxia-induced autophagy and EMT of CRL-7566 cells. Inhibiting the NF-κB signaling pathway weakened the effect of PDCD4 knockdown on hypoxia-induced autophagy and EMT of CRL-7566 cells. Conclusion MiR-150-5p silencing inhibited hypoxia-induced autophagy and EMT of endometriotic cells by regulating the PDCD4/NF-κB signaling pathway.
Overgrazing has become one of the main factors affecting grassland degradation over the past two decades in China. To solve this problem, the government has implemented a grassland ecological compensation policy and grazing monitoring system that is highly dependent on rural cadres. However, few studies have analyzed the impact of political status (rural cadres' identity) on overgrazing. This study reveals the impact of political status on herders' overgrazing behavior. It evaluates the moderating effect of social capital on this impact using a linear regression model based on survey data from 640 herder households in Inner Mongolia, Gansu, and Qinghai, China. The results show that herders with political status are more likely to overgraze. The level of trust in rural cadres has a positive moderating effect on the influence of political status on herders' overgrazing. Small farms with political status are more likely to overgraze compared to large farms. Grazing monitoring by local government can reduce the overgrazing of herders with political status and weaken the positive effects of political status and the trust level in rural cadres regarding overgrazing. Therefore, local governments should monitor more strictly grazing activities for herders with political status, especially those with small grassland scales, and pay more attention to the role of herders' social capital in constructing a sustainable grassland governance mechanism.
The geographical distribution imbalance of global agricultural land has been reduced as a result of increasing globalization, which accelerates land redistribution through global supply networks. In turn, interregional trade extends the control of land resources beyond of local borders. However, the specific structural features of agricultural land flow patterns embodied in international trade remain unclear from the perspective of a complex network. In this paper, we integrate multi-regional input-output model and complex network theory to reveal the structural characteristics of the global embodied land flow network (GELFN) in multiple dimensions. Globally, GELFN exhibits small-world nature, indicating that embodied land transfer interconnects economies at a high level. Regionally, GELFN has a basic community structure of seven groups, and economies in the same regional economic cooperation organizations, such as NAFTA, EU and AU, are more likely to cluster in the same community, implying that GELFN embodies the characteristics of multi-polarization and intra-region aggregation. Nationally, by introducing resource endowments and network-based measurements, we classify seven groups of key economies (‘connection clusters’) to identify different land use patterns. Moreover, the core-periphery structure of GELFN confirms that a few economies act as hubs associated with a large amount of land transfer. The results emphasize the importance of multi-regional cooperation on global agricultural land management and well-targeted policies in key economies and sectors.
Non-expresser of pathogenesis-related genes 1 (NPR1) has been demonstrated to be a master transcription factor during resistance against pathogens, the mechanisms by which regulates chilling stress, however, remain unclear. Our results revealed that the expression and protein content of SlNPR1 were dramatically induced by low temperature (4 °C). CRISPR/Cas9-mediated SlNPR1 mutagenesis aggravated the symptoms of chilling injury in tomato plant, which was accompanied with the accumulation of malonic dialdehyde (MDA), hydrogen peroxide (H2O2) and superoxide anion (O2⁻), and the decrease of soluble protein content, proline content as well as antioxidant enzymes activity. In addition, slnpr1 mutants showed lower expression of SlICE1 and SlCBF1 in contrast to wild type plants (WT). PAL, C4H, C3H and COMT genes play important roles in the synthesis of ferulic acid (FA). We found that knockout of SlNPR1 reduced the expression of PAL, C4H, C3H and COMT induced by low temperature (4 °C) and inhibited the accumulation of FA content. Interestingly, FA-treated plants showed greater tolerance to chilling stress and displayed higher expression of SlICE1 and SlCBF1, exhibited lower levels of MDA and H2O2, but higher antioxidant enzyme (APX, POD, SOD and CAT) activity than WT. These findings reveal a new regulatory pathway that SlNPR1 enhances tolerance to chilling stress in tomato plant by alleviating oxidative damage and affecting the synthesis of FA.
Let S be an n-dimensional vector space over the finite field Fq, where q is necessarily a prime power. Denote Kq(n,k) (resp. Jq(n,k)) to be the q-Kneser graph (resp. Grassmann graph) for k⩾1 whose vertices are the k-dimensional subspaces of S and two vertices v1 and v2 are adjacent if dim(v1∩v2)=0 (resp. dim(v1∩v2)=k−1). We consider the infection spreading in the q-Kneser graphs and the Grassmann graphs: a vertex gets infected if it has at least two infected neighbors. In this paper, we compute the P3-hull numbers of Kq(n,k) and Jq(n,k) respectively, which is the minimum size of a vertex set that eventually infects the whole graph.
The interest of policymakers in community management of tropical forests is ever growing. Yet, a large research body shows varied levels of success of community conservation initiatives. While policymakers often prioritize legal forest ownership, mostly land titles, consensus exists that success rather depends on a broader set of local institutional arrangements and their fit with the forest context. In this paper, we contribute to building theory on these institutional arrangements and their interaction. We apply a fuzzy set Qualitative Comparative Analysis to case study data on 12 voluntary community conservation initiatives in northern Peru to explore the relationship between local enforcement, legal and alternative property rights, and conservation effectiveness. As recommended for QCA our case selection was intentional and the cases exhibit diverse conservation successes, geographic characteristics, legal and customary property rights, and enforcement mechanisms. We conclude that strong community enforcement mechanisms are indispensable for effective conservation in voluntary initiatives. Furthermore, we find for cases with strong enforcement mechanisms, that some government back-up, i.e., local government support for enforcement and/or legal rights to conserve the forest, significantly increases conservation effectiveness. Strong conservation enforcement tends to be present in communities with strong forest rules, leaders, and pre-existing community institutions. Our findings suggest the importance of paying close attention to community characteristics during project design and refraining from one-size-fits-all-solutions, such as focusing mainly on the presence of legal ownership rights over the forest. Instead, more focus needs to be placed on understanding existing community institutions and supporting communities to strengthen and adapt these for conservation enforcement, rather than imposing new arrangements. Finally, policymakers can help community enforcement institutions become even more effective, by providing them with legal rights to conserve the forest and by strengthening their relationship with local governments so that they receive support in situations they struggle to handle alone.
Let V be an n-dimensional vector space over the finite field Fq, and [Vk] denote the family of all k-dimensional subspaces of V. The families F1⊆[Vk1],F2⊆[Vk2],…,Fr⊆[Vkr] are said to be r-cross t-intersecting if dim(F1∩F2∩⋯∩Fr)≥t for all Fi∈Fi,1≤i≤r. The r-cross t-intersecting families F1, F2,…,Fr are said to be non-trivial if dim(∩1≤i≤r∩F∈FiF)<t. In this paper, we first determine the structure of r-cross t-intersecting families with maximum product of their sizes. As a consequence, we partially prove one of Frankl and Tokushige's conjectures about r-cross 1-intersecting families for vector spaces. Then we describe the structure of non-trivial r-cross t-intersecting families F1, F2,…,Fr with maximum product of their sizes under the assumptions r=2 and F1=F2=⋯=Fr=F, respectively, where the F in the latter assumption is well known as r-wise t-intersecting family. Meanwhile, stability results for non-trivial r-wise t-intersecting families are also been proved.
The Chinese government has declared a determination at the 75th United Nations General Assembly that China will improve its independent contribution and adopt more powerful measures to peak the carbon emissions before 2030. However, such strict implementation of carbon reduction policies is bound to bring the cost of sacrificing economic development. In such a context, this paper tries to use shadow price to measure the average social cost of emission reduction, marginal abatement cost to depict the pressure to reduce carbon emissions based on non-radial distance function, and provides an optimal scheme for provincial emission reduction to minimize the national cost of emission reduction based on variable-coefficient model. Results show that: First, the average value of shadow price is 15.91 and varies widely among regions, which means on average reducing one unit of carbon emissions will sacrifice 15.914 yuan RMB of economic output, and there exists possibility of carbon transactions across regions; Second, on the one hand, marginal abatement cost of carbon emission for most regions presents an upward tendency over time, which means greater economic costs have to be sacrificed with economic development in the future; On the other hand, marginal abatement cost is much higher in regions with high economic level than that in the economically undeveloped areas, which indicates reducing carbon emissions is becoming increasingly difficult and would pay more economical cost in economically developed regions; Third, the optional allocation scheme of CO2 reduction derived from this research is better than administrative ways of Grandfathering and Benchmarking in terms of minimizing emission reduction cost. Results of this paper indicate that larger carbon trading market can be implemented in China to economically fulfill the commitment of peaking carbon emissions.
Rare events are those with a small occurrence probability, but might have a substantial impact. Despite their potential importance, previous research hardly considers rare events because of the difficulty of handling long-tail information. We propose a solution that incorporates a large-scale topic model to extract them from customer opinions and network inference to select high-impact variables. We test our model by analyzing hotel reviews. The result indicates that some of the rare events (e.g., “misleading description”, “home feeling”) can be highly influential to customer ratings or recommendations, which helps marketers sharpen their understanding of consumers and redesign their services accordingly.
As deforestation has become an increasingly urgent issue worldwide, global initiatives and national policies have been launched to reduce deforestation. However, existing measures pay little attention to indirect deforestation and consumers' responsibilities, overlooking the different roles played by countries in the trading network. Therewith, to identify the producer's and consumers' responsibilities for deforestation, and reveal the roles and interrelations of those countries in the trading system, this study applies input-output analysis to find the main producers and consumers of embodied deforestation and complex network method to construct a network to illustrate the interrelations of the countries and identify their roles in the network. The results show the United States, China, Germany and other developed countries are the main consumers while Canada, Brazil, Indonesia and other heavily forested countries are the critical providers of embodied deforestation. Further studies find these countries have the highest level of degree, strength, and centrality, dominating the trade activities in the network. Additionally, the network features small-world nature and heterogeneity, illustrating the close connection of the network and the decisive roles of key nodes. This analysis provides findings to help policymakers more effectively address deforestation worldwide, by highlighting the flow of resources to and from key economies which have previously been overlooked.
The effects of transmembrane (TMEM) proteins in the progression of prostate cancer (PCa) remain unknown. This study aims to explore the functions of TMEM100 in PCa. To explore the expression, regulation, and effects of TMEM100 in PCa, two PCa cell lines and 30 PCa tissue samples with adjacent control tissues were examined. Online databases, immunohistochemistry, immunofluorescence, western blot, flow cytometry, colony formation, wound healing, transwell assays, and xenograft mouse models were used to explore effects of TMEM100 relevant to PCa. TMEM100 expression was shown to decrease in PCa patients, and low TMEM100 expression was associated with tumor stage and metastasis. Overexpression of TMEM100 suppressed PCa progression by inhibiting the FAK/PI3K/AKT signaling pathway. Tumor size was smaller in TMEM100 overexpressing PCa cells in xenograft mice than in control mice. We also found that TMEM100 could regulate SCNN1D by inhibiting FAK/PI3K/AKT signaling in PCa cell lines. Taken together, our findings indicate that TMEM100 is a tumor suppressor that plays a vital role in preventing PCa proliferation, migration, and invasion through inhibition of FAK/PI3K/AKT signaling. These studies suggest that TMEM100 can be used as a predictive biomarker and therapeutic target.
Sensitivity analysis (SA) is used to identify the effects of crop model input parameters on model results. Previous studies have indicated that the CERES-Maize model was difficult to calibrate under the different water stress conditions. A genetic parameters time-series sensitivity analysis is needed to guide parameter optimization. The objectives of this study were to: (i) comprehensively quantify the genetic parameters in CERES-Maize based on the extended Fourier amplitude sensitivity test. The sensitivity of CERES-Maize output variables was analyzed under different water stress conditions; (ii) determine the sensitivities of output variables to genetic parameters during the growth period. The results demonstrated that output variable sensitivity varied in response to different water stress conditions. The total sensitivity index (TSI) and time-dependent TSI of crop parameters were more sensitive than the first sensitivity index (FOSI) and time-dependent FOSI of crop genetic parameters. The sensitivities of two years (2013 and 2014) based on FOSI and time-series FOSI were consistent; some differences existed between simulations based on TSI and time-series TSI. Under different water management conditions, the sensitivity of phyllochron interval (PHINT) to biomass decreased earlier and faster when drought occurred in the early growth period (D1 and D2). The time series of sensitivity index was consistent with the CK treatment when drought happened in the later growth periods (D3 and D2). The two parameters of PHINT and thermal time from emergence to end of juvenile (P1) were most sensitive to leaf area index (LAI) when drought occurred in the early growth periods (D1 and D2). In addition to PHINT and P1, other parameters also had sensitivities for LAI when drought occurred in later growth periods (D3 and D4). Future studies should focus on the response of dynamic output variable to soil parameters and weather conditions over the growing season in order to calibrate and apply the CERES-Maize model.
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