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This study assesses the impact of simulated sea level rise (SLR) on mercury distribution and migration in an urban mangrove wetland on the northern coast of Maluan Bay, Xiamen City, Fujian Province, China. Two adjacent Kandelia obovata mangrove plots with elevations representing current sea level and a 40-cm SLR were examined. Total mercury (THg), methylmercury (MeHg), and mercury isotopes in sediments from different elevations were analyzed to reveal the geochemical behavior of mercury under a simulated 100-year SLR scenario. THg and MeHg distribution in sediments mirrored patterns of biogenic elements (carbon, nitrogen, and phosphorus), suggesting adsorption onto organic matter as the primary entry mechanism. Low-elevation plots showed significantly higher concentrations of THg, MeHg, total organic carbon (TOC), total nitrogen (TN), and total phosphorus (TP) compared to high-elevation plots. Mercury isotope characteristics indicated that the primary mercury source was anthropogenic emissions from surrounding lands, entering the wetland from both landward and seaward directions. The study highlights the crucial role of mangrove wetlands in mercury pollution control and nutrient cycling under SLR conditions. Results suggest that SLR enhances the retention capacity of mangrove wetlands for THg, MeHg, and nutrients. This research provides a scientific basis for mangrove conservation and restoration, offering new insights into the geochemical behavior of mercury in vegetated intertidal ecosystems in the context of climate change. [ABSTRACT FROM AUTHOR]

Vitamins are dietary components necessary for cellular metabolic balance, especially redox homeostasis; deficient or excessive supply may give rise to symptoms of psychiatric disorders. Exploring the nutritional and metabolic pathways of vitamins could contribute to uncovering the underlying pathogenesis of ferroptosis-associated diseases. This mini-review aims to provide insights into vitamins closely linked to the regulation of ferroptosis from the perspective of cellular reactive oxygen species biology. The mainstream reprogramming mechanisms of ferroptosis are overviewed, focusing on unique biological processes of iron metabolism, lipid metabolism, and amino acid metabolism. Moreover, recent breakthroughs in therapeutic interventions targeting ferroptosis via fully utilizing vitamin-based pharmacological tools were overviewed, covering vitamins (B, C, E, and K). Finally, mechanism insight related to vitamin-associated nutrient signaling was provided, highlighting the pharmacological benefits of metabolically reprogramming ferroptosis-associated diseases. [ABSTRACT FROM AUTHOR]

We consider the scheduling of battery charging of electric vehicles (EVs) integrated with renewable power generation. The increasing adoption of EVs and the development of renewable energies contribute importance to this research. The optimization of charging scheduling is challenging because of the large action space, the multi-stage decision making, and the high uncertainty. To solve this problem is time-consuming when the scale of the system is large. It is urgent to develop a practical and efficient method to properly schedule the charging of EVs. The contribution of this work is threefold. First, we provide a sufficient condition on which the charging of EVs can be completely self-sustained by distributed generation. An algorithm is proposed to obtain the optimal charging policy when the sufficient condition holds. Second, the scenario when the supply of the renewable power generation is deficient is investigated. We prove that when the renewable generation is deterministic there exists an optimal policy which follows the modified least laxity and longer remaining processing time first (mLLLP) rule. Third, we provide an adaptive rule-based algorithm which obtains a near-optimal charging policy efficiently in general situations. We test the proposed algorithm by numerical experiments. The results show that it performs better than the other existing rule-based methods. [ABSTRACT FROM AUTHOR]

The genus Silurus, an important group of catfish, exhibits heterogeneous distribution in Eurasian freshwater systems. This group includes economically important and endangered species, thereby attracting considerable scientific interest. Despite this interest, the lack of a comprehensive phylogenetic framework impedes our understanding of the mechanisms underlying the extensive diversity found within this genus. Herein, we analyzed 89 newly sequenced and 20 previously published mitochondrial genomes (mitogenomes) from 13 morphological species to reconstruct the phylogenetic relationships, biogeographic history, and species diversity of Silurus. Our phylogenetic reconstructions identified eight clades, supported by both maximum-likelihood and Bayesian inference. Sequence-based species delimitation analyses yielded multiple molecular operational taxonomic units (MOTUs) in several taxa, including the Silurus asotus complex (four MOTUs) and Silurus microdorsalis (two MOTUs), suggesting that species diversity is underestimated in the genus. A reconstructed time-calibrated tree of Silurus species provided an age estimate of the most recent common ancestor of approximately 37.61 million years ago (Ma), with divergences among clades within the genus occurring between 11.56 Ma and 29.44 Ma, and divergences among MOTUs within species occurring between 3.71 Ma and 11.56 Ma. Biogeographic reconstructions suggested that the ancestral area for the genus likely encompassed China and the Korean Peninsula, with multiple inferred dispersal events to Europe and Central and Western Asia between 21.78 Ma and 26.67 Ma and to Japan between 2.51 Ma and 18.42 Ma. Key factors such as the Eocene-Oligocene extinction event, onset and intensification of the monsoon system, and glacial cycles associated with sea-level fluctuations have likely played significant roles in shaping the evolutionary history of the genus Silurus. [ABSTRACT FROM AUTHOR]

Alzheimer’s disease (AD) is one of the most common chronic neurodegenerative diseases. Hyperphosphorylated tau plays an indispensable role in neuronal dysfunction and synaptic damage in AD. Proteolysis-targeting chimeras (PROTACs) are a novel type of chimeric molecule that can degrade target proteins by inducing their polyubiquitination. This approach has shown promise for reducing tau protein levels, which is a potential therapeutic target for AD. Compared with traditional drug therapies, the use of PROTACs to reduce tau levels may offer a more specific and efficient strategy for treating AD, with fewer side effects. In the present study, we designed and synthesized a series of small-molecule PROTACs to knock down tau protein. Of these, compound C8 was able to lower both total and phosphorylated tau levels in HEK293 cells with stable expression of wild-type full-length human tau (termed HEK293-htau) and htau-overexpressed mice. Western blot findings indicated that C8 degraded tau protein through the ubiquitin–proteasome system in a time-dependent manner. In htau-overexpressed mice, the results of both the novel object recognition and Morris water maze tests revealed that C8 markedly improved cognitive function. Together, our findings suggest that the use of the smallmolecule PROTAC C8 to degrade phosphorylated tau may be a promising therapeutic strategy for AD. [ABSTRACT FROM AUTHOR]

Porcine epidemic diarrhea (PED) is a highly contagious intestinal infection primarily affecting pigs. It is caused by the porcine epidemic diarrhea virus (PEDV). PEDV targets the villus tissue cells in the small intestine and mesenteric lymph nodes, resulting in shortened intestinal villi and, in extreme cases, causing necrosis of the intestinal lining. Moreover, PEDV infection can disrupt the balance of the intestinal microflora, leading to an overgrowth of harmful bacteria like Escherichia coli. Exosomes, tiny membrane vesicles ranging from 30 to 150 nm in size, contain a complex mixture of RNA and proteins. MicroRNA (miRNA) regulates various cell signaling, development, and disease progression processes. This study extracted exosomes from both groups and performed high-throughput miRNA sequencing and bioinformatics techniques to investigate differences in miRNA expression within exosomes isolated from PEDV-infected porcine small intestine tissue compared to healthy controls. Notably, two miRNA types displayed upregulation in infected exosomes, while 12 exhibited downregulation. These findings unveil abnormal miRNA regulation patterns in PEDV-infected intestinal exosomes, shedding light on the intricate interplay between PEDV and its host. This will enable further exploration of the relationship between thesemiRNA changes and signaling pathways, enlightening PEDV pathogenesis and potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Porcine epidemic diarrhea (PED) is a highly contagious intestinal infection primarily affecting pigs. It is caused by the porcine epidemic diarrhea virus (PEDV). PEDV targets the villus tissue cells in the small intestine and mesenteric lymph nodes, resulting in shortened intestinal villi and, in extreme cases, causing necrosis of the intestinal lining. Moreover, PEDV infection can disrupt the balance of the intestinal microflora, leading to an overgrowth of harmful bacteria like Escherichia coli. Exosomes, tiny membrane vesicles ranging from 30 to 150 nm in size, contain a complex mixture of RNA and proteins. MicroRNA (miRNA) regulates various cell signaling, development, and disease progression processes. This study extracted exosomes from both groups and performed high-throughput miRNA sequencing and bioinformatics techniques to investigate differences in miRNA expression within exosomes isolated from PEDV-infected porcine small intestine tissue compared to healthy controls. Notably, two miRNA types displayed upregulation in infected exosomes, while 12 exhibited downregulation. These findings unveil abnormal miRNA regulation patterns in PEDV-infected intestinal exosomes, shedding light on the intricate interplay between PEDV and its host. This will enable further exploration of the relationship between thesemiRNA changes and signaling pathways, enlightening PEDV pathogenesis and potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Objectives: A retrospective analysis of the clinical outcomes of personalized interventions for type 2 diabetes mellitus (T2DM) in an interdisciplinary team. Methods: Under the guidance of an interdisciplinary team, 40 patients with T2DM underwent a systematic examination at the beginning of the intervention, 3 months after the intervention, and 3 months of follow-up at the end of the intervention (i.e., at 6 months). Key indicators such as fasting plasma glucose (FPG), 2-hour postprandial glucose (2hPG), fasting insulin level (FINS), glycated hemoglobin (HbA1c), blood lipids, and body mass index (BMI) were measured. Results: After the 3-month intervention, participants' BMI, FPG, 2hPG, FINS, and HbA1c improved significantly, with statistically significant differences (P<0.05).These metrics remained essentially stable at the 3-month follow-up. Of all the participants, 92.5% (37 cases in total) successfully discontinued their medication after 3 months of intervention, of which 80% (32 cases) remained stable during the 3-month follow-up after discontinuation, fulfilling the criteria for remission of T2DM; 2 cases successfully reduced the dose of their medication, and only 1 case was maintained on the original treatment. Conclusions: Through an interdisciplinary team intervention strategy, we significantly optimized the glucose metabolism, lipid metabolism, and BMI status of patients with T2DM, making diabetes remission an achievable goal, which provides valuable experience for further optimization of diabetes prevention and control protocols. [ABSTRACT FROM AUTHOR]

Background and aims: Obesity is one of the most prevalent diseases worldwide with less ideal approved agents in clinic. Activating the HSF1/PGC-1a axis in adipose tissues has been reported to induce thermogenesis in mice, which presents a promising therapeutic avenue for obesity treatment. The present study aimed to identified novel natural HSF1 activator and evaluated the therapeutic effects of the newly discovered compound on obesity-associated metabolic disorders and the molecular mechanisms of these effects. Methods: Our previous reported HSF1/PGC-1a activator screening system was used to identify novel natural HSF1 activator. The PGC-1a luciferase activity, immunoblot, protein nuclear-translocation, immunofluorescence, chromatin immunoprecipitation assays were used to evaluate the activity of compound HN-001 in activating HSF1. The experiments of mitochondrial number measurement, TG assay and imaging, cellular metabolic assay, gene assays, and CRISPR/Cas 9 were applied for investigating the metabolic effect of HN-001 in C3H10-T1/2 adipocytes. The in vivo anti-obesity efficacies and beneficial metabolic effects of HN-001 were evaluated by performing body and fat mass quantification, plasma chemical analysis, GTT, ITT, cold tolerance test, thermogenesis analysis. Results: HN-001 dose- and time-dependently activated HSF1 and induced HSF1 nuclear translocation, resulting in an enhancement in binding with the gene Pgc-1a. This improvement induced activation of adipose thermogenesis and enhancement of mitochondrial oxidation capacity, thus inhibiting adipocyte maturation. Deletion of HSF1 in adipocytes impaired mitochondrial oxidation and abolished the above beneficial metabolic effects of HN-001, including adipocyte browning induction, improvements in mitogenesis and oxidation capacity, and lipid-lowering ability. In mice, HN-001 treatment efficiently alleviated diet-induced obesity and metabolic disorders. These changes were associated with increased body temperature in mice and activation of the HSF1/PGC-1a axis in adipose tissues. UCP1 expression and mitochondrial biogenesis were increased in both white and brown adipose tissues of HN-001-treated mice. Conclusion: These data indicate that HN-001 may have therapeutic potential for obesity-related metabolic diseases by increasing the capacity of energy expenditure in adipose tissues through a mechanism involving the HSF1/PGC-1a axis, which shed new light on the development of novel anti-obesity agents derived from marine sources. [ABSTRACT FROM AUTHOR]

Faculty members' research performance holds great significance for the development of a university. The primary objective of this study is to examine the influences of researchers' personalities on their research performance within universities, as well as the mediating role of research engagement in this relationship. The study encompassed 189 faculty members from a university and employed descriptive statistics, correlation analysis, measurement, and structural equation modeling as the analytical procedures. The results obtained from structural equation modeling reveal significant effects of faculty members' personalities on their objective research performance rather than self-reported performance. Specifically, conscientiousness and openness to experience exhibit a positive correlation with research performance. On the contrary, the neuroticism and social attributes of personality (the integration of extraversion and agreeableness) exhibit a negative correlation with research performance. Furthermore, research engagement mediates the effects of openness to experience and neuroticism on research performance. This study carries significant implications for the training and recruitment selection of faculty members in universities and enhances our understanding of how different personalities lead to a variance in research engagement and performance. [ABSTRACT FROM AUTHOR]

Consensus clustering is gaining increasing attention for its high quality and robustness. In particular, k-means-based Consensus Clustering (KCC) converts the usual computationally expensive problem to a classic k-means clustering with generalized utility functions, bringing potentials for large-scale data clustering on different types of data. Despite KCC's applicability and generalizability, implementing this method such as representing the binary dataset in the k-means heuristic is challenging and has seldom been discussed in prior work. To fill this gap, we present a MATLAB package, KCC, that completely implements the KCC framework and utilizes a sparse representation technique to achieve a low space complexity. Compared to alternative consensus clustering packages, the KCC package is of high flexibility, efficiency, and effectiveness. Extensive numerical experiments are also included to show its usability on real-world datasets. [ABSTRACT FROM AUTHOR]

Sepsis is the primary cause of acute kidney injury (AKI) and is associated with high mortality rates. Growing evidence suggests that noncoding RNAs are vitally involved in kidney illnesses, whereas the role of circular RNAs (circRNAs) in sepsis-induced AKI (SAKI) remains largely unknown. In this present study, caecal ligation and puncture (CLP) in mice was performed to establish an SAKI model. The expression of circRNAs and mRNAs was analysed using circRNA microarray or nextgeneration sequencing. The results revealed that the expressions of 197 circRNAs and 2509 mRNAs were dysregulated. Validation of the selected circRNAs was performed by qRT-PCR. Bioinformatics analyses and chromatin immunoprecipitation demonstrated that NF-B/p65 signalling induced the upregulation of circC3, circZbtb16, and circFkbp5 and their linear counterparts by p65 transcription in mouse tubular epithelial cells (mTECs). Furthermore, competitive endogenous RNA (ceRNA) networks demonstrated that some components of NF-B signalling were potential targets of these dysregulated circRNAs. Among them, Tnf-a was increased by circFkbp5 through the downregulation of miR-760-3p in lipopolysaccharide (LPS)-stimulated mTECs. Knocking down circFkbp5 inhibited the p65 phosphorylation and apoptosis in injured mTECs. These findings suggest that the selected circRNAs and the related ceRNA networks provide new knowledge into the fundamental mechanism of SAKI and circFkbp5/miR-760-3p/Tnf-a axis might be therapeutic targets. [ABSTRACT FROM AUTHOR]

Background: There was no literature showed superior provenance or clone of B. alnoides selected for the development of southern Fujian, as well as no suitable reforestation mixed pattern for B. alnoides developed for preventing the trunk pests effectively. It is significant to select an optimal reforestation pattern for B. alnoides to be expanded in southern Fujian. Methods: The tissue-cultured seedlings of Betula alnoides were introduced to south-east China for reforestation mixed pattern tests. B. alnoides was admixed with Castanopsis hystrix with five patterns at Wanshiqing Area and admixed with Cunninghamia lanceolata with four patterns at Beijing Area. A sample plot of 20 m Ã--30 m was set in each experimental treatment and each tree was investigated in the sample plot, including tree height (m), DBH (cm), pests and diseases and freeze injury. Result: The effects of the pure forest were better than that of the cluster mixed forest in tree height. The cluster mixed pattern was not beneficial to the tree height growth of B. alnoides and DBH growth of C. lanceolata in early stage. The average annual growth of B. alnoides in tree height, DBH and individual volume achieved 2.2-2.5 m, 2.8-3.0 cm and 0.0061-0.0074 m³, respectively. [ABSTRACT FROM AUTHOR]

While hippocampal atrophy and its regional susceptibility to Alzheimer's disease (AD) are well reported at late stages of AD, studies of the asymptomatic stage of AD are limited but could elucidate early stage pathophysiology as well as provide predictive biomarkers. In this study, we performed multi-modal magnetic resonance imaging (MRI) to estimate morphometry, functional connectivity, and tissue microstructure of hippocampal subfields in cognitively normal adults including those with asymptomatic AD. Highresolution resting-state functional, diffusion and structural MRI, cerebral spinal fluid (CSF), and neuropsychological evaluations were performed in healthy young adults (HY: n = 40) and healthy older adults with negative (HOff: n = 47) and positive (HOC: n = 25) CSF biomarkers of AD. Morphometry, functional connectivity, and tissue microstructure were estimated from the structural, functional, and diffusion MRI images, respectively. Our results indicated that normal aging affected morphometry, connectivity, and microstructure in all hippocampal subfields, while the subiculum and CA1-3 demonstrated the greatest sensitivity to asymptomatic AD pathology. Tau, rather than amyloid-b, was closely associated with imaging-derived synaptic and microstructural measures. Microstructural metrics were significantly associated with neuropsychological assessments. These findings suggest that the subiculum and CA1-3 are the most vulnerable in asymptomatic AD and tau level is driving these early changes. [ABSTRACT FROM AUTHOR]

Mutations in the Aminoadipate-Semialdehyde Synthase (AASS) gene encoding a-aminoadipic semialdehyde synthase lead to hyperlysinemia-I, a benign metabolic variant without clinical significance, and hyperlysinemia-II with developmental delay and intellectual disability. Although both forms of hyperlysinemia display biochemical phenotypes of questionable clinical significance, an association between neurologic disorder and a pronounced biochemical abnormality remains a challenging clinical question. Here, we report that Aass mutant male and female mice carrying the R65Q mutation in a-ketoglutarate reductase (LKR) domain have an elevated cerebral lysine level and a normal brain development, whereas the Aass mutant mice carrying the G489E mutation in saccharopine dehydrogenase (SDH) domain exhibit elevations of both cerebral lysine and saccharopine levels and a smaller brain with defective neuronal development. Mechanistically, the accumulated saccharopine, but not lysine, leads to impaired neuronal development by inhibiting the neurotrophic effect of glucose-6-phosphate isomerase (GPI). While extracellular supplementation of GPI restores defective neuronal development caused by G498E mutation in SDH of Aass. Altogether, our findings not only unravel the requirement for saccharopine degradation in neuronal development, but also provide the mechanistic insights for understanding the neurometabolic disorder of hyperlysinemia-II. [ABSTRACT FROM AUTHOR]

Recent years have witnessed the emergence of worldwide megalopolises and the accompanying public safety events, making urban safety a top priority in modern urban management. Among various threats, dangerous goods such as gas and hazardous chemicals transported through cities have bred repeated tragedies and become the deadly "bomb" we sleep with every day. While tremendous research efforts have been devoted to dealing with dangerous goods transportation (DGT) issues, further study is still in great need to quantify this problem and explore its intrinsic dynamics from a big data perspective. In this article, we present a novel system called DGeye, to feature a fusion between DGT trajectory data and residential population data for dangers perception and prediction. Specifically, DGeye first develops a probabilistic graphical model-based approach to mine spatio-temporally adjacent risk patterns from population-aware risk trajectories. Then, DGeye builds the novel causality network among risk patterns for risk pain-point identification, risk source attribution, and online risky state prediction. Experiments on both Beijing and Tianjin cities demonstrate the effectiveness of DGeye in real-life DGT risk management. As a case in point, our report powered by DGeye successfully drove the government to lay down gas pipelines for the famous Guijie food street in Beijing. [ABSTRACT FROM AUTHOR]

A P(NMe2)3-mediated reductive (1+4) annulation reaction of αketo esters with substituted nitroalkenes has been developed, providing a feasible protocol to construct polysubstituted isoxazoline N-oxides in moderate to excellent yields from readily available starting materials. This reaction originates from the characteristic reactivity of in situ generated KukhtinRamirez adducts and presumably proceeds through a tandem Michael addition-intramolecular SN2 sequence. To further expand the utility of this annulation reaction, isoxazolines have been efficiently prepared from corresponding annulation products upon treatment with trimethyl phosphite. [ABSTRACT FROM AUTHOR]

Employer Brand Evaluation (EBE) is to understand an employer's unique characteristics to identify competitive edges. Traditional approaches rely heavily on employers' financial information, including financial reports and filings submitted to the Securities and Exchange Commission (SEC), which may not be readily available for private companies. Fortunately, online recruitment services provide a variety of employers' information from their employees' online ratings and comments, which enables EBE from an employee's perspective. To this end, in this article, we propose a method named Company Profiling-based Collaborative Topic Regression (CPCTR) to collaboratively model both textual (i.e., reviews) and numerical information (i.e., salaries and ratings) for learning latent structural patterns of employer brands. With identified patterns, we can effectively conduct both qualitative opinion analysis and quantitative salary benchmarking. Moreover, a Gaussian processes-based extension, GPCTR, is proposed to capture the complex correlation among heterogeneous information. Extensive experiments are conducted on three real-world datasets to validate the effectiveness and generalizability of our methods in real-life applications. The results clearly show that our methods outperform state-of-the-art baselines and enable a comprehensive understanding of EBE. [ABSTRACT FROM AUTHOR]

The thermodynamic and kinetic characteristics of CO2 adsorption of SBA-16 loaded with pentaethylenehexamine (PEHA) have been investigated using adsorption column system. The Langmuir isotherm model fitts the CO2 adsorption isotherms well, and the average isosteric heat of adsorption is 59.6 kJ/mol, indicating that the CO2 adsorption on PEHAloaded SBA-16 is chemisorption. The Avrami fractional dynamics model is very suitable for illustrating the adsorption behaviour of CO2 adsorption, and the results of kinetic analysis show that increasing the partial pressure of CO2 or the working temperature is beneficial to the adsorption of CO2. Three desorption methods were evaluatedto achieve the optimal desorption method. The results show that VTSA and steam stripping method are effective methods for industrial CO2 desorption. Steam stripping may be more suitable for plants that already have low-cost steam. The activation energy Ea of CO2 adsorption/desorption is calculated using Arrhenius equation. The activation energy Ea of CO2 adsorption/desorption was calculated using the Arrhenius equation. The results show that the absolute value of Ea (adsorption) decreases with the increase of CO2 partial pressure. In addition, the Ea value of vacuum rotary regeneration method and steam stripping method is smaller than the Ea value of temperature swing regeneration. [ABSTRACT FROM AUTHOR]

Purpose: A nonlinear finite element method was applied to examine the effects of implant diameter and length on the maximum von Mises stresses in the jaw, and to evaluate the maximum displacement of the implant-abutment complex in immediateloading models. Materials and Methods: The implant diameter (D) ranged from 3.0 to 5.0 mm and implant length (L) ranged from 6.0 to 16.0 mm. Results: The results showed that the maximum von Mises stress in cortical bone was decreased by 65.8% under a buccolingual load with an increase in D. In cancellous bone, it was decreased by 71.5% under an axial load with an increase in L. The maximum displacement in the implant-abutment complex decreased by 64.8% under a buccolingual load with an increase in D. The implant was found to be more sensitive to L than to D under axial loads, while D played a more important role in enhancing its stability under buccolingual loads. Conclusion: When D exceeded 4.0 mm and L exceeded 11.0 mm, both minimum stress and displacement were obtained. Therefore, these dimensions were the optimal biomechanical selections for immediate-loading implants in type B/2 bone. [ABSTRACT FROM AUTHOR]

Objectives: Long non-coding RNAs (lncRNAs) are characterized as a group of RNAs that more than 200 nucleotides in length and have no protein-coding function. More and more evidences provided that lncRNAs serve as key molecules in the development of cancer. Deregulation of lncRNAs functions as either oncogenes or tumour suppressor genes in various diseases. Recently, increasing studies about PANDAR in cancer progression were reported. In our review, we will focus on the current research on the character of PANDAR include the clinical management, tumour progression and molecular mechanisms in human cancers. Materials and methods: We summarize and analyze current studies concerning the biological functions and mechanisms of lncRNA PANDA in tumour development. The related studies were obtained through a systematic search of Pubmed. Results: PANDAR was a well-characterized oncogenic lncRNA and widely overexpressed in many tumours. PANDAR is upregulated in many types of cancer, including colorectal cancer, lung cancer, renal cell carcinoma, cholangiocarcinoma, osteosarcoma, thyroid cancer and other cancers. Upregulation of PANDAR was significantly associated with advanced tumour weights, TNM stage and overall survival. Furthermore, repressed of PANDAR would restrain proliferation, migration and invasion. Conclusion: PANDAR may act as a powerful tumour biomarker for cancer diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Interactions between the brain networks and subnetworks are crucial for active and resting cognitive states. Whether a subnetwork can restore the adequate function of the parent network whenever a disease state affects the parent network is unclear. Investigations suggest that the control of the anterior insula-based network (AIN) over the default-mode network (DMN) and central-executive network (CEN) is decreased in individuals with mild cognitive impairment (MCI). Here, we hypothesized that the posterior insula-based network (PIN) attempts to compensate for this decrease. To test this, we compared a group of MCI and normal cognitive individuals. A dynamical causal modeling method has been employed to investigate the dynamic network controls/modulations. We used the resting state functional MRI data, and assessed the interactions of the AIN and of the PIN, respectively, over the DMN and CEN. We found that the greater control of AIN than that of DMN (Wilcoxon rank sum: Z = 1.987; p = 0.047) and CEN (Z = 3.076; p = 0.002) in normal group and the lower (impaired) control of AIN than that of CEN (Z = 8.602; p = 7.816 1018). We further revealed that the PIN control was significantly higher than that of DMN (Z = 6.608; p = 3.888 10 11) and CEN (Z = 6.429; p = 1.278 1010) in MCI group where the AIN was impaired, but that control was significantly lower than of DMN (Z = 5.285; p = 1.254 107) and CEN (Z = 5.404; p = 6.513 10 8) in normal group. Finally, the global cognitive test score assessed using Montreal cognitive assessment and the network modulations were correlated (Spearman's correlation: r = 0.47; p = 3.76 10 5 and r = 0.43; p = 1.97 104). These findings might suggest the flexible functional profiles of AIN and PIN in normal aging and MCI. [ABSTRACT FROM AUTHOR]

Background: African Americans have been reported to have a higher prevalence of Alzheimer's disease (AD) than Caucasians, but etiology-specific AD biomarkers have not been systematically analyzed in older African Americans. Coexisting cerebrovascular disease may also contribute to this increased prevalence. We hypothesized that cerebrospinal fluid (CSF) biomarkers of amyloid, neurodegeneration, and endothelial dysfunction would differ between older African Americans and Caucasians with normal cognition and cognitive impairment associated with AD. Methods: We prospectively recruited 135 older Americans to undergo detailed clinical, neuropsychological, genetic, magnetic resonance imaging (MRI), and CSF analysis from 2013 to 2015 at Emory University (Atlanta, GA, USA). We compared levels of CSF markers for β-amyloid (Aβ42, Aβ40), total and phosphorylated tau (t-tau and p-tau181, respectively), endothelial dysfunction (soluble vascular cell adhesion molecule 1, soluble intercellular adhesion molecule 1), α-synuclein, and neurodegeneration (neurofilament light chain [NfL]), as well as MRI markers, for hippocampal atrophy and cerebrovascular disease (white matter hyperintensity [WMH] volume). Results: Sixty-five older African Americans (average age, 69.1 years) and 70 older Caucasians (average age, 70.8 years) were included. After adjusting for demographic variables, AD risk alleles, and cognitive function, older African Americans had lower CSF levels of p-tau181 (difference of 7.4 pg/ml; 95% CI, 3.7-11.2 pg/ml; p < 0.001), t-tau (difference of 23.6 pg/ml; 95% CI, 9.5-37.7; p = 0.001), and Aβ40 (difference of 1.35 ng/ml; 95% CI, 0.29-2.42 ng/ml; p = 0.013) despite similar levels of Aβ42, NfL, WMH volume, and hippocampal volume. Cognitively impaired African Americans also had lower CSF t-tau/Aβ42 (difference of 0.255 per 1-SD change in composite cognition; 95% CI, 0.100-0.409; p = 0. 001) and p-tau181/Aβ42 (difference of 0.076 per 1-SD change in composite cognition; 95% CI, 0.031-0.122; p = 0.001). These could not be explained by measured biomarkers of non-AD processes, but African Americans may be more susceptible than Caucasians to the cognitive effects of WMH. Conclusions: Despite comparable levels of CSF Aβ42 and Aβ42/Aβ40, cognitive impairment in African Americans is associated with smaller changes in CSF tau markers but greater impact from similar WMH burden than Caucasians. Race-associated differences in CSF tau markers and ratios may lead to underdiagnosis of AD in African Americans. [ABSTRACT FROM AUTHOR]

This article develops an analytic framework to analyze the tradeoff between economic efficiency and distributional equity in targeting payments for ecosystem services (PES). It also proposes an empirical procedure to trace out the efficiency-equity frontier, where the program is Pareto optimal in the sense that it cannot be improved upon to achieve either higher efficiency or distributional equity without compromising the other. We apply the procedure to the Conservation Reserve Program (CRP), the largest PES program in U.S. history, to analyze (a) whether it is possible to improve both the efficiency and the distributional equity of the program, and (b) what the choice made by CRP administrators implies about the political-economic balance. Results reveal that (a) CRP administrators forfeited about 9% of efficiency for an 18%-23% improvement in distributional equity, depending on the equity indicator used, in the eighteenth signup of the CRP; (b) reducing the maximum allowable rental rate for all contracts would improve efficiency at the cost of distributional equity; (c) reducing the maximum county enrollment cap would reduce efficiency without generating much improvement in distributional equity; and (d) the CRP targeting criterion could be redesigned to achieve both higher efficiency and higher distributional equity. [ABSTRACT FROM AUTHOR]

In traditional localization methods for synthetic aperture radar (SAR), the range sum estimation and Doppler centroid estimation (DCE) are required. The DCE error can influence the localization accuracy greatly. In addition, the target height information cannot be obtained by these methods. In this paper, a three-dimensional localization method for multistatic SAR based on the numerical range-Doppler (RD) algorithm and entropy minimization principle is proposed. In this method, the raw data from each transmitter and receiver (T/R) pair are focused by the numerical RD algorithm with the initial location value of the reference target. Then, Newton iteration is used to solve the target location value with the information of the bistatic range sum (BRS) in different SAR images with respect to different T/R pairs. Generally, the initial location value of the reference target is not accurate, and it can influence the imaging quality and accuracy of other target locations. We use entropy to measure image quality and iterate imaging with the new location value of the reference target, until the entropy gets the minimum value. Therefore, we can get the optimal location value of the reference target, which can make image entropy reach the minimum. Finally, all targets can be located by the Newton iteration method with their BRS in each T/R pair that are obtained from the images with minimum entropy. Compared with traditional localization methods for monostatic SAR, the proposed method not only effectively eliminates the influences of DCE errors, but also can get the target height information. Therefore, it improves the localization accuracy and can achieve three-dimensional localization. The effectiveness of the localization approach is validated by a numerical simulation experiment. [ABSTRACT FROM AUTHOR]

The article discusses the problems of studying ambiguous words in the second language. Particular focus is given to the function of inhibitory control in word learning and the significance of semantics. Other topics addressed include the relation between semantics and ambiguous words and the lexical representation of words.

This article integrates economic and biophysical models to assess how federal crop revenue insurance programs affect land use, cropping systems, and environmental quality in the U.S. Corn Belt region. The empirical framework includes econometric models that predict land conversion and crop choices at the parcel level based on expectation and variance of crop revenues, land quality, climate conditions, and physical characteristics at each site. The predictions are then combined with sitespecific environmental production functions to determine the effect of revenue insurance on nitrate runoff and leaching, soil water and wind erosion, and carbon sequestration. Results suggest that federal crop insurance has, on average, a small effect on conversions of non-cropland to cropland, and somewhat more significant impacts on crop choice and crop rotation. These changes in cropping systems have, on average, small impacts on agricultural pollution. [ABSTRACT FROM AUTHOR]

Economic development in rural areas affects the natural environment, which in turn affects economic growth--both rural and urban. These shared interests and feedback effects in the natural environment are increasingly recognized as important economic and political issues, and necessitate a new framework for better understanding them. This article asks why such a framework does not exist and why it should be developed. It then presents such a framework by integrating regional, urban, and environmental economic insights. The framework focuses on the interactive location decisions of firms and households and centripetal forces for concentration and centrifugal forces for decentralization. The article captures the economic and environmental consequences of rural-urban relocation and feedback effects through changes in agglomeration economies, congestion costs, natural and social amenities, and the location of economic opportunities. Results show that some feedback effects reinforce the initial forces, but others weaken them. We present two examples to demonstrate the application of the framework. The first focuses on how agglomeration economies affect the effectiveness of environmental regulation and illustrates the benefits of incorporating regional and urban economic insights into environmental policy analysis. The second example focuses on how conservation policy can create localized amenities that help resource-rich regions avoid the natural resource curse and illustrates how concepts and perspectives from resource and environmental economics can improve our understanding of regional and rural issues. [ABSTRACT FROM AUTHOR]

Economic development in rural areas affects the natural environment, which in turn affects economic growth—both rural and urban. These shared interests and feedback effects in the natural environment are increasingly recognized as important economic and political issues, and necessitate a new framework for better understanding them. This article asks why such a framework does not exist and why it should be developed. It then presents such a framework by integrating regional, urban, and environmental economic insights. The framework focuses on the interactive location decisions of firms and households and centripetal forces for concentration and centrifugal forces for decentralization. The article captures the economic and environmental consequences of rural-urban relocation and feedback effects through changes in agglomeration economies, congestion costs, natural and social amenities, and the location of economic opportunities. Results show that some feedback effects reinforce the initial forces, but others weaken them. We present two examples to demonstrate the application of the framework. The first focuses on how agglomeration economies affect the effectiveness of environmental regulation and illustrates the benefits of incorporating regional and urban economic insights into environmental policy analysis. The second example focuses on how conservation policy can create localized amenities that help resource-rich regions avoid the natural resource curse and illustrates how concepts and perspectives from resource and environmental economics can improve our understanding of regional and rural issues. [ABSTRACT FROM AUTHOR]

Possibilistic fuzzy c-means (PFCM) is used for solving the problem of data classification. It relies on initial cluster centers set by users that are lack of theoretical supporting. Inappropriate initial values may result in deviation of cluster centers. In this paper, A Robust Adaptive Particle Swarm Optimization based on steepest descent method is proposed to solve the problem of initialization and improving the performance of clustering. Combined with clustering algorithm, particle swarm optimization (PSO) possesses the good robustness to noises. Furthermore, since traditional PSO is inefficient when searching in the complex nonlinear hyperspace. Steepest descend method is applied to adaptively adjusting parameters. Moreover, optimum combined position is used to update the current information of each particle, which can discover more useful information lies in personal optimal experience and global optimal experience. The performance of proposed algorithm are tested in numerical simulations. The effectiveness, accuracy and stability of the new model are verified by simulations both with and without noises. [ABSTRACT FROM AUTHOR]

Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Background: Umbilical cord blood (UCB) not only contains hematopoietic stem cells (HSCs), but also non-hematopoietic stem cells (NHSCs) that are able to differentiate into a number of distinct cell types. Based on studies published to date, the frequency of NHSCs in UCB is believed to be very low. However, the isolation of these cells is primarily based on their adhesion to tissue culture plastic surfaces. Methods and results: In the current study, we demonstrate that this approach overlooks some of the extremely immature NHSCs because they lack the ability to adhere to plastic. Using a native extracellular matrix (ECM), produced by bone marrow (BM) stromal cells, the majority of the UCB-NHSCs attached within 4 h. The colony-forming unit fibroblast frequency of these cells was 1.5 x 104/108 mononuclear cells, which is at least 4000-fold greater than previously reported for UCB-NHSCs. The phenotype of these cells was fibroblast-like and different from those obtained by plastic adhesion; they formed embryonic body-like clusters that were OCT4-positive and expressed other human embryonic stem cell-related markers. Importantly, when implanted subcutaneously for 8 weeks into immunocompromised mice, these ECM-adherent and expanded NHSCs generated three germ layer-derived human tissues including muscle, fat, blood vessel, bone, gland, and nerve. Moreover, injection of these cells into muscle damaged by cryoinjury significantly accelerated muscle regeneration. Conclusions: These results indicate that UCB may be a virtually unlimited source of NHSCs when combined with isolation and expansion on ECM. NHSCs may be a practical alternative to embryonic stem cells for a number of therapeutic applications. [ABSTRACT FROM AUTHOR]

Advances in smartphone technology have promoted the rapid development of mobile apps. However, the availability of a huge number of mobile apps in application stores has imposed the challenge of finding the right apps to meet the user needs. Indeed, there is a critical demand for personalized app recommendations. Along this line, there are opportunities and challenges posed by two unique characteristics of mobile apps. First, appmarkets have organized apps in a hierarchical taxonomy. Second, apps with similar functionalities are competing with each other. Although there are a variety of approaches for mobile app recommendations, these approaches do not have a focus on dealing with these opportunities and challenges. To this end, in this article, we provide a systematic study for addressing these challenges. Specifically, we develop a structural user choice model (SUCM) to learn fine-grained user preferences by exploiting the hierarchical taxonomy of apps as well as the competitive relationships among apps. Moreover, we design an efficient learning algorithm to estimate the parameters for the SUCM model. Finally, we perform extensive experiments on a large app adoption dataset collected from Google Play. The results show that SUCM consistently outperforms state-of-the-art Top-N recommendation methods by a significant margin. [ABSTRACT FROM AUTHOR]