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Resveratrol, a phytochemical found in various plants and Chinese herbs, is associated with multiple tumor-suppressing activities, has been tested in clinical trials. However, the molecular mechanisms involved in resveratrol-mediated tumor suppressing activities are not yet completely defined. Here, we showed that treatment with resveratrol inhibited cell mobility through induction of the mesenchymal–epithelial transition (MET) in lung cancer cells. We also found that downregulation of FOXC2 (forkhead box C2) is critical for resveratrol-mediated suppression of tumor metastasis in an in vitro and in vivo models. We also identified a signal cascade, namely, resveratrol—∣miRNA-520h—∣PP2A/C—∣Akt → NF-κB → FOXC2, in which resveratrol inhibited the expression of FOXC2 through regulation of miRNA-520h-mediated signal cascade. This study identified a new miRNA-520h-related signal cascade involved in resveratrol-mediated tumor suppression activity and provide the clinical significances of miR-520h, PP2A/C and FOXC2 in lung cancer patients. Our results indicated a functional link between resveratrol-mediated miRNA-520h regulation and tumor suppressing ability, and provide a new insight into the role of resveratrol-induced molecular and epigenetic regulations in tumor suppression.

Ketamine, an N -methyl- D -aspartate receptor (NMDAR) channel blocker, has been found to induce rapid and robust antidepressant-like effects in rodent models and in treatment-refractory depressed patients. However, the marked acute psychological side effects of ketamine complicate the interpretation of both preclinical and clinical data. Moreover, the lack of controlled data demonstrating the ability of ketamine to sustain the antidepressant response with repeated administration leaves the potential clinical utility of this class of drugs in question. Using quantitative electroencephalography (qEEG) to objectively align doses of a low-trapping NMDA channel blocker, AZD6765 (lanicemine), to that of ketamine, we demonstrate the potential for NMDA channel blockers to produce antidepressant efficacy without psychotomimetic and dissociative side effects. Furthermore, using placebo-controlled data, we show that the antidepressant response to NMDA channel blockers can be maintained with repeated and intermittent drug administration. Together, these data provide a path for the development of novel glutamatergic-based therapeutics for treatment-refractory mood disorders.

The unique characteristic of head and neck squamous cell carcinoma (HNSCC) is that local invasion rather than distant metastasis is the major route for dissemination. Therefore, targeting the locally invasive cancer cells is more important than preventing systemic metastasis in HNSCC and other invasive-predominant cancers. We previously demonstrate a specific mechanism for HNSCC local invasion: the epithelial–mesenchymal transition (EMT) regulator Twist1 represses microRNA let-7i expression, leading to the activation of the small GTPase Rac1 and engendering the mesenchymal-mode movement in three-dimensional (3D) culture. However, targeting the EMT regulator is relatively difficult because of its transcription factor nature and the strategy for confining HNSCC invasion to facilitate local treatment is limited. Imipramine blue (IB) is a newly identified anti-invasive compound that effectively inhibits glioma invasion. Here we demonstrate that in HNSCC cells, a noncytotoxic dose of IB represses mesenchymal-mode migration in two-and-a-half-dimensional/3D culture system. IB suppresses EMT and stemness of HNSCC cells through inhibition of Twist1-mediated let-7i downregulation and Rac1 activation and the EMT signalling. Mechanistically, IB inhibits reactive oxygen species-induced nuclear factor-κB pathway activation. Importantly, IB promotes degradation of the EMT inducer Twist1 by enhancing F-box and leucine-rich repeat protein 14 (FBXL14)-mediated polyubiquitination of Twist1. Together, this study demonstrates the potent anti-invasion and EMT-inhibition effect of IB, suggesting the potential of IB in treating local invasion-predominant cancers.

MicroRNAs (miRNAs) are small RNAs that suppress gene expression by their interaction with 3’untranslated region of specific target mRNAs. Although the dysregulation of miRNAs has been identified in human cancer, only a few of these miRNAs have been functionally documented in breast cancer. Thus, defining the important miRNA and functional target involved in chemoresistance is an urgent need for human breast cancer treatment. In this study, we, for the first time, identified a key role of miRNA 520h (miR-520h) in drug resistance. Through protecting cells from paclitaxel-induced apoptosis, expression of miR-520h promoted the drug resistance of human breast cancer cells. Bioinformatics prediction, compensatory mutation and functional validation further confirmed the essential role of miR-520h-suppressed Death-associated protein kinase 2 (DAPK2) expression, as restoring DAPK2 abolished miR-520h-promoted drug resistance, and knockdown of DAPK2 mitigated cell death caused by the depletion of miR-520h. Furthermore, we observed that higher level of miR-520h is associated with poor prognosis and lymph node metastasis in human breast cancer patients. These results show that miR-520h is not only an independent prognostic factor, but is also a potential functional target for future applications in cancer therapeutics.

Intra-granular Acicular Ferrite (IAF), as one of the most well-known desirable microstructure of ferrite with a chaotic crystallographic orientation, can not only refine the microstructure and retard the propagation of cleavage crack but also provide excellent combination of strength and toughness in steel. The effect of adding cerium on microstructure and controlling proper cerium-based inclusions in order to improve properties in low-carbon commercial steel (SS400) were investigated. The type of inclusions can be controlled by changing S/O ratio and Ce content. Without Ce modification, MnS is a dominate inclusion. After adding Ce, the stable inclusion phases change from AlCeO 3 to Ce 2 O 2 S. The optimum amount of cerium, 0.0235 wt.%, lead in proper grain refinement and formation of cerium oxide, oxy-sulfide and sulfide inclusions. Having a high amount of cerium results in increasing the number of inclusions significantly as a result it cannot be effective enough and the inclusions will act like barriers for others. It is found that the inclusions with a size of about 4∼7 μm can serve as heterogeneous nucleation sites for AF formation. Thermodynamic calculations have been applied to predict the inclusion formation in this molten steel as well, which show a good agreement with experimental one.

Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attractive tool. Within this context, we assimilate satellite soil moisture (SM) retrievals from the Advanced Microwave Scanning Radiometer (AMSR-E), the Advanced Scatterometer (ASCAT) and the Soil Moisture and Ocean Salinity (SMOS) instrument, using an Ensemble Kalman filter to improve operational flood prediction within a large (> 40 000 km2) semi-arid catchment in Australia. We assess the importance of accounting for channel routing and the spatial distribution of forcing data by applying SM-DA to a lumped and a semi-distributed scheme of the probability distributed model (PDM). Our scheme also accounts for model error representation by explicitly correcting bias in soil moisture and streamflow in the ensemble generation process, and for seasonal biases and errors in the satellite data. Before assimilation, the semi-distributed model provided a more accurate streamflow prediction (Nash–Sutcliffe efficiency, NSE = 0.77) than the lumped model (NSE = 0.67) at the catchment outlet. However, this did not ensure good performance at the \"ungauged\" inner catchments (two of them with NSE below 0.3). After SM-DA, the streamflow ensemble prediction at the outlet was improved in both the lumped and the semi-distributed schemes: the root mean square error of the ensemble was reduced by 22 and 24%, respectively; the false alarm ratio was reduced by 9% in both cases; the peak volume error was reduced by 58 and 1%, respectively; the ensemble skill was improved (evidenced by 12 and 13% reductions in the continuous ranked probability scores, respectively); and the ensemble reliability was increased in both cases (expressed by flatter rank histograms). SM-DA did not improve NSE. Our findings imply that even when rainfall is the main driver of flooding in semi-arid catchments, adequately processed satellite SM can be used to reduce errors in the model soil moisture, which in turn provides better streamflow ensemble prediction. We demonstrate that SM-DA efficacy is enhanced when the spatial distribution in forcing data and routing processes are accounted for. At ungauged locations, SM-DA is effective at improving some characteristics of the streamflow ensemble prediction; however, the updated prediction is still poor since SM-DA does not address the systematic errors found in the model prior to assimilation.

The general relationships between vegetation and water yield under different climatic regimes are well established at a small watershed scale in the past century. However, applications of these basic theories to evaluate the regional effects of land cover change on water resources remain challenging due to the complex interactions of vegetation and climatic variability and hydrologic processes at the large scale. The objective of this study was to explore ways to examine the spatial and temporal effects of a large ecological restoration project on water yield across the Loess Plateau region in northern China. We estimated annual water yield as the difference between precipitation input and modelled actual evapotranspiration (ET) output. We constructed a monthly ET model using published ET data derived from eddy flux measurements and watershed streamflow data. We validated the ET models at a watershed and regional levels. The model was then applied to examine regional water yield under land cover change and climatic variability during the implementation of the Grain-for-Green (GFG) project during 1999–2007. We found that water yield in 38% of the Loess Plateau area might have decreased (1–48 mm per year) as a result of land cover change alone. However, combined with climatic variability, 37% of the study area might have seen a decrease in water yield with a range of 1–54 mm per year, and 35% of the study area might have seen an increase with a range of 1–10 mm per year. Across the study region, climate variability masked or strengthened the water yield response to vegetation restoration. The absolute annual water yield change due to vegetation restoration varied with precipitation regimes with the highest in wet years, but the relative water yield changes were most pronounced in dry years. We concluded that the effects of land cover change associated with ecological restoration varied greatly over time and space and were strongly influenced by climatic variability in the arid region. The current regional vegetation restoration projects have variable effects on local water resources across the region. Land management planning must consider the influences of spatial climate variability and long-term climate change on water yield to be more effective for achieving environmental sustainability.

Hunger is a complex behavioural state that elicits intense food seeking and consumption. These behaviours are rapidly recapitulated by activation of starvation-sensitive AGRP neurons, which present an entry point for reverse-engineering neural circuits for hunger. Here we mapped synaptic interactions of AGRP neurons with multiple cell populations in mice and probed the contribution of these distinct circuits to feeding behaviour using optogenetic and pharmacogenetic techniques. An inhibitory circuit with paraventricular hypothalamus (PVH) neurons substantially accounted for acute AGRP neuron-evoked eating, whereas two other prominent circuits were insufficient. Within the PVH, we found that AGRP neurons target and inhibit oxytocin neurons, a small population that is selectively lost in Prader–Willi syndrome, a condition involving insatiable hunger. By developing strategies for evaluating molecularly defined circuits, we show that AGRP neuron suppression of oxytocin neurons is critical for evoked feeding. These experiments reveal a new neural circuit that regulates hunger state and pathways associated with overeating disorders. Using optogenetic and pharmacogenetic techniques, the authors find that AGRP neurons suppress oxytocin-releasing neurons, which is a critical interaction for evoked feeding; thus they identify a circuit potentially involved in regulating hunger state. Neural aspects of feeling hungry Stimulation of neurons expressing agouti-related peptide (AGRP) in the hypothalamus of mice evokes the behavioural responses to hunger — an intense search for food and copious eating. Taking advantage of the fact that these starvation-sensitive neurons are accessible to genetic manipulation, this study 'reverse engineers' a neural circuit for hunger, using optogenetics and pharmacogenetics. AGRP-expressing neurons are shown to suppress oxytocin-releasing neurons, a small neuronal population that is lost in Prader–Willi syndrome, a condition involving insatiable hunger. The inhibitory circuit involving oxytocin neurons is a prerequisite for AGRP-expressing-neuron-evoked eating, a finding that establishes this previously unknown neural circuit in the regulation of the hunger state and pathways associated with overeating disorders.

The thalamus and its nuclei are largely indistinguishable on standard T1 or T2 weighted MRI. While diffusion tensor imaging based methods have been proposed to segment the thalamic nuclei based on the angular orientation of the principal diffusion tensor, these are based on echo planar imaging which is inherently limited in spatial resolution and suffers from distortion. We present a multi-atlas segmentation technique based on white-matter-nulled MP-RAGE imaging that segments the thalamus into 12 nuclei with computation times on the order of 10 min on a desktop PC; we call this method THOMAS (THalamus Optimized Multi Atlas Segmentation). THOMAS was rigorously evaluated on 7T MRI data acquired from healthy volunteers and patients with multiple sclerosis by comparing against manual segmentations delineated by a neuroradiologist, guided by the Morel atlas. Segmentation accuracy was very high, with uniformly high Dice indices: at least 0.85 for large nuclei like the pulvinar and mediodorsal nuclei and at least 0.7 even for small structures such as the habenular, centromedian, and lateral and medial geniculate nuclei. Volume similarity indices ranged from 0.82 for the smaller nuclei to 0.97 for the larger nuclei. Volumetry revealed that the volumes of the right anteroventral, right ventral posterior lateral, and both right and left pulvinar nuclei were significantly lower in MS patients compared to controls, after adjusting for age, sex and intracranial volume. Lastly, we evaluated the potential of this method for targeting the Vim nucleus for deep brain surgery and focused ultrasound thalamotomy by overlaying the Vim nucleus segmented from pre-operative data on post-operative data. The locations of the ablated region and active DBS contact corresponded well with the segmented Vim nucleus. Our fast, direct structural MRI based segmentation method opens the door for MRI guided intra-operative procedures like thalamotomy and asleep DBS electrode placement as well as for accurate quantification of thalamic nuclear volumes to follow progression of neurological disorders. •White-matter nulled MP-RAGE sequence provides improved intra-thalamic contrast.•THOMAS exploits this improved contrast to segment 12 thalamic nuclei with excellent accuracy as measured by Dice against manual segmentation.•Volumetry results using THOMAS revealed atrophy of select nuclei in multiple sclerosis patients.•THOMAS can also be used to accurately predict the ventralis intermedius nucleus for deep brain stimulation targeting.

Extreme haze episodes repeatedly shrouded Beijing during the winter of 2012–2013, causing major environmental and health problems. To better understand these extreme events, we performed a model-assisted analysis of the hourly observation data of PM2.5 and its major chemical compositions. The synthetic analysis shows that (1) the severe winter haze was driven by stable synoptic meteorological conditions over northeastern China, and not by an abrupt increase in anthropogenic emissions. (2) Secondary species, including organics, sulfate, nitrate, and ammonium, were the major constituents of PM2.5 during this period. (3) Due to the dimming effect of high loading of aerosol particles, gaseous oxidant concentrations decreased significantly, suggesting a reduced production of secondary aerosols through gas-phase reactions. Surprisingly, the observational data reveals an enhanced production rate of secondary aerosols, suggesting an important contribution from other formation pathways, most likely heterogeneous reactions. These reactions appeared to be more efficient in producing secondary inorganics aerosols than organic aerosols resulting in a strongly elevated fraction of inorganics during heavily polluted periods. (4) Moreover, we found that high aerosol concentration was a regional phenomenon. The accumulation process of aerosol particles occurred successively from cities southeast of Beijing. The apparent sharp increase in PM2.5 concentration of up to several hundred μg m−3 per hour recorded in Beijing represented rapid recovery from an interruption to the continuous pollution accumulation over the region, rather than purely local chemical production. This suggests that regional transport of pollutants played an important role during these severe pollution events.