2D ferroelectric material has emerged as an attractive building block for high‐density data storage nanodevices. Although monolayer van der Waals ferroelectrics have been theoretically predicted, a ...key experimental breakthrough for such calculations is still not realized. Here, hexagonally stacking α‐In2Se3 nanoflake, a rarely studied van der Waals polymorph, is reported to exhibit out‐of‐plane (OOP) and in‐plane (IP) ferroelectricity at room temperature. Ferroelectric multidomain states in a hexagonal α‐In2Se3 nanoflake with uniform thickness can survive to 6 nm. Most strikingly, the electric‐field‐induced polarization switching and hysteresis loop are, respectively, observed down to the bilayer and monolayer (≈1.2 nm) thicknesses, which designates it as the thinnest layered ferroelectric and verifies the corresponding theoretical calculation. In addition, two types of ferroelectric nanodevices employing the OOP and IP polarizations in 2H α‐In2Se3 are developed, which are applicable for nonvolatile memories and heterostructure‐based nanoelectronics/optoelectronics.
The thinnest layered ferroelectric is demonstrated for the first time at room temperature. The semiconducting hexagonal α‐In2Se3 nanoflakes exhibit out‐of‐plane and in‐plane ferroelectricity that are closely intercorrelated. The polarization switching and hysteresis loops can be realized in the thickness as thin as ≈2.3 nm (bilayer) and ≈1.2 nm (monolayer). Two types of ferroelectric switchable devices are proposed to show the potential application in nonvolatile memories.
MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the ...miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.
Two-dimensional transition metal dichalcogenide nanoribbons are touted as the future extreme device downscaling for advanced logic and memory devices but remain a formidable synthetic challenge. ...Here, we demonstrate a ledge-directed epitaxy (LDE) of dense arrays of continuous, self-aligned, monolayer and single-crystalline MoS
nanoribbons on β-gallium (III) oxide (β-Ga
O
) (100) substrates. LDE MoS
nanoribbons have spatial uniformity over a long range and transport characteristics on par with those seen in exfoliated benchmarks. Prototype MoS
-nanoribbon-based field-effect transistors exhibit high on/off ratios of 10
and an averaged room temperature electron mobility of 65 cm
V
s
. The MoS
nanoribbons can be readily transferred to arbitrary substrates while the underlying β-Ga
O
can be reused after mechanical exfoliation. We further demonstrate LDE as a versatile epitaxy platform for the growth of p-type WSe
nanoribbons and lateral heterostructures made of p-WSe
and n-MoS
nanoribbons for futuristic electronics applications.
Connectome-based predictive modeling (CPM; Finn et al., 2015; Shen et al., 2017) was recently developed to predict individual differences in traits and behaviors, including fluid intelligence (Finn ...et al., 2015) and sustained attention (Rosenberg et al., 2016a), from functional brain connectivity (FC) measured with fMRI. Here, using the CPM framework, we compared the predictive power of three different measures of FC (Pearson's correlation, accordance, and discordance) and two different prediction algorithms (linear and partial least square PLS regression) for attention function. Accordance and discordance are recently proposed FC measures that respectively track in-phase synchronization and out-of-phase anti-correlation (Meskaldji et al., 2015). We defined connectome-based models using task-based or resting-state FC data, and tested the effects of (1) functional connectivity measure and (2) feature-selection/prediction algorithm on individualized attention predictions. Models were internally validated in a training dataset using leave-one-subject-out cross-validation, and externally validated with three independent datasets. The training dataset included fMRI data collected while participants performed a sustained attention task and rested (N = 25; Rosenberg et al., 2016a). The validation datasets included: 1) data collected during performance of a stop-signal task and at rest (N = 83, including 19 participants who were administered methylphenidate prior to scanning; Farr et al., 2014a; Rosenberg et al., 2016b), 2) data collected during Attention Network Task performance and rest (N = 41, Rosenberg et al., in press), and 3) resting-state data and ADHD symptom severity from the ADHD-200 Consortium (N = 113; Rosenberg et al., 2016a). Models defined using all combinations of functional connectivity measure (Pearson's correlation, accordance, and discordance) and prediction algorithm (linear and PLS regression) predicted attentional abilities, with correlations between predicted and observed measures of attention as high as 0.9 for internal validation, and 0.6 for external validation (all p's < 0.05). Models trained on task data outperformed models trained on rest data. Pearson's correlation and accordance features generally showed a small numerical advantage over discordance features, while PLS regression models were usually better than linear regression models. Overall, in addition to correlation features combined with linear models (Rosenberg et al., 2016a), it is useful to consider accordance features and PLS regression for CPM.
•Functional connectivity can predict individual differences in attention.•We compared different connectivity measures and feature selection algorithms.•Four different data sets permitted both internal and external validation.•For rest data, PLS regression models were numerically better than linear regression.•Pearson’s correlation, accordance, and discordance did not meaningfully differ.
Sarcopenia, a gradual loss of muscle mass and function, has been associated with poor health outcomes. Its correlation with another age-related degenerative process, impaired cognition, remains ...uncertain. This meta-analysis aimed to determine whether there is an association between sarcopenia and cognitive impairment.
PubMed and Scopus were searched for observational studies that investigated the association between sarcopenia and cognitive dysfunction. Participants' demographics and measurements, definition of sarcopenia, and tools for evaluating cognitive function were retrieved. The correlations between sarcopenia and cognitive impairment were expressed as crude and adjusted odds ratios with 95% confidence intervals (CIs).
Seven cross-sectional studies comprising 5994 participants were included. The crude and adjusted odds ratios were 2.926 (95% CI, 2.297-3.728) and 2.246 (95% CI, 1.210-4.168), respectively. The subgroup analysis showed that different target populations and sex specificity did not significantly modify the association, whereas the tools for evaluating cognitive function and modalities for measuring body composition did.
Sarcopenia was independently associated with cognitive impairment. Future cohort studies are warranted to clarify the causal correlation. The inclusion of relevant biomarkers and functional measurements is also recommended to elucidate the underlying biological mechanism.
Critically-ill surgical patients are at higher risk for sarcopenia, which is associated with worse survival. Sarcopenia may impair the respiratory musculature, which can subsequently influence the ...outcome of ventilator weaning. Although there are a variety of weaning parameters predictive of weaning outcomes, none have tried to incorporate "muscle strength" or "sarcopenia". The aim of the current study was to explore the association between sarcopenia and difficult-to-wean (DtW) in critically-ill surgical patients. The influence of sarcopenia on ICU mortality was also analyzed.
Ninety-six patients undergoing mechanical ventilation in the surgical intensive care unit (ICU) were enrolled. Demographic data and weaning parameters were recorded from the prospectively collected database, and the total psoas muscle area (TPA) was determined at the level of the 3rd lumbar vertebra by computed tomography. Sarcopenia was defined by previously established cut-off points and its influence on clinical outcomes was examined. Receiver operating characteristic (ROC) curve analysis was conducted to investigate the predictive capability of TPA and weaning parameters for predicting weaning outcomes.
The median age of the studied patients was 73 years. Thirty patients (31.3%) were sarcopenic and 30 (31.3%) were defined as DtW. Eighteen patients (18.8%) had ICU mortality. Multivariate logistic regression analyses revealed that sarcopenia was an independent risk factor for DtW and ICU mortality. The area under the ROC curve (AUC) of TPA for predicting successful weaning was 0.727 and 0.720 in female and male patients, respectively. After combining TPA and conventional weaning parameters, the AUC for DtW increased from 0.836 to 0.911 and from 0.835 to 0.922 in female and male patients, respectively.
Sarcopenia is an independent risk factor for DtW and ICU mortality. TPA has predictive value when assessing weaning outcomes and can be used as an effective adjunct predictor along with conventional weaning parameters.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Poly(p-phenylenevinylene)s (PPVs), a staple of the conductive polymer family, consist of alternating alkene and phenyl groups in conjugation. The physical properties of this organic material are ...intimately linked to the cis/trans configuration of the alkene groups. While many synthetic methods afford PPVs with all-trans stereochemistry, very few deliver the all-cis congeners. We report herein a synthesis of all-cis PPVs with living characteristics via stereoretentive ring-opening metathesis polymerization (ROMP). Exquisite catalyst control allows for the preparation of homopolymers or diblock copolymers with perfect stereoselectivity, narrow dispersities, and predictable average molar masses. All-cis PPVs can then serve as light-responsive polymers through clean photoisomerization of the stilbenoid units.
Monolayer molybdenum disulfide (MoS2) has become a promising building block in optoelectronics for its high photosensitivity. However, sulfur vacancies and other defects significantly affect the ...electrical and optoelectronic properties of monolayer MoS2 devices. Here, highly crystalline molybdenum diselenide (MoSe2) monolayers have been successfully synthesized by the chemical vapor deposition (CVD) method. Low-temperature photoluminescence comparison for MoS2 and MoSe2 monolayers reveals that the MoSe2 monolayer shows a much weaker bound exciton peak; hence, the phototransistor based on MoSe2 presents a much faster response time (<25 ms) than the corresponding 30 s for the CVD MoS2 monolayer at room temperature in ambient conditions. The images obtained from transmission electron microscopy indicate that the MoSe exhibits fewer defects than MoS2. This work provides the fundamental understanding for the differences in optoelectronic behaviors between MoSe2 and MoS2 and is useful for guiding future designs in 2D material-based optoelectronic devices.
The aim of the present study was to verify the effects of fluoxetine on dysregulation of apoptosis and invasive potential in human hepatocellular carcinoma (HCC) SK-Hep1 and Hep3B cells. Cells were ...treated with different concentrations of fluoxetine for different times. MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) assays were used for testing the effects of fluoxetine on cell viability. The regulation of apoptosis signaling, and anti-apoptotic, proliferation, and metastasis-associated proteins after fluoxetine treatment were assayed by flow cytometry and Western blotting assay. The detection of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation after fluoxetine treatment was performed by NF-κB reporter gene assay. The results demonstrated that fluoxetine significantly reduced cell viability, cell migration/invasion, NF-κB, extracellular signal-regulated kinases (ERK) activation, and expression of anti-apoptotic (Cellular FLICE (FADD-like IL-1β-converting enzyme)-inhibitory protein (C-FLIP), Myeloid cell leukemia-1 (MCL-1), X-Linked inhibitor of apoptosis protein (XAIP), and Survivin), proliferation (Cyclin-D1), angiogenesis (vascular endothelial growth factor (VEGF)), and metastasis-associated proteins (matrix metalloproteinase-9 (MMP-9)). Fluoxetine also significantly induced apoptosis, unregulated extrinsic (activation of first apoptosis signal protein and ligand (Fas/FasL), and caspase-8) and intrinsic (loss of mitochondrial membrane potential (ΔΨm) pathways and increased Bcl-2 homologous antagonist killer (BAK) apoptosis signaling. Taken together, these results demonstrated that fluoxetine induced apoptosis through extrinsic/intrinsic pathways and diminished ERK/NF-κB-modulated anti-apoptotic and invasive potential in HCC cells in vitro.
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