Abstract
RNA-seq experiments previously performed by our laboratories showed enrichment in intronic sequences and alterations in alternative splicing in dengue-infected human cells. The transcript of ...the SAT1 gene, of well-known antiviral action, displayed higher inclusion of exon 4 in infected cells, leading to an mRNA isoform that is degraded by non-sense mediated decay. SAT1 is a spermidine/spermine acetyl-transferase enzyme that decreases the reservoir of cellular polyamines, limiting viral replication. Delving into the molecular mechanism underlying SAT1 pre-mRNA splicing changes upon viral infection, we observed lower protein levels of RBM10, a splicing factor responsible for SAT1 exon 4 skipping. We found that the dengue polymerase NS5 interacts with RBM10 and its sole expression triggers RBM10 proteasome-mediated degradation. RBM10 over-expression in infected cells prevents SAT1 splicing changes and limits viral replication, while its knock-down enhances the splicing switch and also benefits viral replication, revealing an anti-viral role for RBM10. Consistently, RBM10 depletion attenuates expression of interferon and pro-inflammatory cytokines. In particular, we found that RBM10 interacts with viral RNA and RIG-I, and even promotes the ubiquitination of the latter, a crucial step for its activation. We propose RBM10 fulfills diverse pro-inflammatory, anti-viral tasks, besides its well-documented role in splicing regulation of apoptotic genes.
•Wavelet packet transform were applied to vibration signal for roughness monitoring.•Monitoring of roughness using a single sensor without other information sources.•Three diverse wavelet packet ...methods were compared using forty mother wavelets.•The optimal wavelet packets for roughness were found in specific frequency ranges.•Packet feature extraction was analysed to determine the optimum decomposition level.
The wavelet packet transform method decomposes a time signal into several independent time-frequency signals called packets. This enables the temporary location of transient events occurring during the monitoring of the cutting processes, which is advantageous in monitoring condition and fault diagnosis. This paper proposes the monitoring of surface roughness using a single low cost sensor that is easily implemented in numerical control machine tools in order to make on-line decisions on workpiece surface finish quality. Packet feature extraction in vibration signals was applied to correlate the sensor signals to measured surface roughness. For the successful application of the WPT method, mother wavelets, packet decomposition level, and appropriate packet selection methods should be considered, but are poorly understood aspects in the literature. In this novel contribution, forty mother wavelets, optimal decomposition level, and packet reduction methods were analysed, as well as identifying the effective frequency range providing the best packet feature extraction for monitoring surface finish. The results show that mother wavelet biorthogonal 4.4 in decomposition level L3 with the fusion of the orthogonal vibration components (ax+ay+az) were the best option in the vibration signal and surface roughness correlation. The best packets were found in the medium-high frequency DDA (6250–9375Hz) and high frequency ADA (9375–12500Hz) ranges, and the feed acceleration component ay was the primary source of information. The packet reduction methods forfeited packets with relevant features to the signal, leading to poor results for the prediction of surface roughness. WPT is a robust vibration signal processing method for the monitoring of surface roughness using a single sensor without other information sources, satisfactory results were obtained in comparison to other processing methods with a low computational cost.
A single‐atom Pt1/CeO2 catalyst formed by atom trapping (AT, 800 °C in air) shows excellent thermal stability but is inactive for CO oxidation at low temperatures owing to over‐stabilization of Pt2+ ...in a highly symmetric square‐planar Pt1O4 coordination environment. Reductive activation to form Pt nanoparticles (NPs) results in enhanced activity; however, the NPs are easily oxidized, leading to drastic activity loss. Herein we show that tailoring the local environment of isolated Pt2+ by thermal‐shock (TS) synthesis leads to a highly active and thermally stable Pt1/CeO2 catalyst. Ultrafast shockwaves (>1200 °C) in an inert atmosphere induced surface reconstruction of CeO2 to generate Pt single atoms in an asymmetric Pt1O4 configuration. Owing to this unique coordination, Pt1δ+ in a partially reduced state dynamically evolves during CO oxidation, resulting in exceptional low‐temperature performance. CO oxidation reactivity on the Pt1/CeO2_TS catalyst was retained under oxidizing conditions.
A highly active and robust single‐atom Pt1/CeO2 catalyst was developed for CO oxidation by tailoring the local environment of isolated Pt2+ through thermal‐shock synthesis (see picture). Ultrafast shockwaves in an inert atmosphere generated Pt single atoms in an asymmetric Pt1O4 configuration, resulting in greatly enhanced low‐temperature activity that was retained under oxidizing conditions.
Summary
Background and Aims
Little is known about the extent of mitochondrial respiratory chain (MRC) activity dysfunction in patients with alcoholic hepatitis (AH). We aimed to assess the hepatic ...MRC activity in AH patients and its potential impact on the severity and prognosis of this life‐threatening liver disease.
Methods
MRC complexes were measured in liver biopsies of 98 AH patients (non‐severe, 17; severe, 81) and in 12 histologically normal livers (NL). Severity was assessed according to Maddrey's Index and MELD score. Corticosteroid response rate and cumulative mortality were also evaluated.
Results
The activity of the five MRC complexes was markedly decreased in the liver of AH patients compared with that of NL subjects, being significantly lower in patients with severe AH than in those with non‐severe AH. There was a negative correlation between the activity of all MRC complexes and the severity of AH. Interestingly, only complex I and III activities showed a significant positive correlation with the corticosteroid response rate and a significant negative correlation with the mortality rate at all‐time points studied. In a multivariate regression analysis, besides the MELD score and the corticosteroid response rate, complex I activity was significantly associated with 3‐month mortality (OR = 6.03; p = 0.034) and complex III activity with 6‐month mortality (OR = 4.70; p = 0.041) in AH patients.
Conclusion
Our results indicate that MRC activity is markedly decreased in the liver of AH patients, and, particularly, the impairment of MRC complexes I and III activity appears to have a significant impact on the clinical outcomes of patients with AH.
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Challenging conventional wisdom that s‐block organometallic reagents such as Grignard or organolithiums need to be used under protecting inert atmosphere (N2 or Ar), employing dry organic solvents ...with a strict temperature control, this Minireview focusses on recent advances on the use of these commodity reagents while operating under air, at room temperature and in the presence of moisture. Key for the success of these approaches has been the use of the following sustainable solvents: i) water; ii) Deep Eutectic Solvents (DESs); or iii) biomass‐derived polyols (like glycerol) or ethereal solvents i. e., 2‐MeTHF or cyclopentyl methyl ether (CPME). The versatility of these air and moisture compatible synthetic protocols has been demonstrated for a myriad of key organic transformations, including nucleophilic additions of RLi/RMgX reagents to unsaturated organic molecules (i. e., ketones, imines, esters, amides or nitriles) as well as ortho‐ and lateral lithiation of aromatic substrates, Pd catalysed cross‐couplings and anionic polymerisation of styrenes. Extension of these studies to lithium amides (LiNR2) or phosphides (LiPPh2) has enabled the development of more sustainable and efficient methods for C−N and C−P bond forming processes. These unconventional s‐block metal mediated transformations have also been successfully incorporated in one‐pot tandem processes in combination with transition‐metal and organo‐catalysis. Remarkably, in some cases the conversions and chemoselectivities observed are superior to those detected in common toxic organic solvents, while working under inert atmosphere conditions with strict temperature control. The key role played by the choice of solvent in these transformations and how it can affect the constitution of the s‐block organometallic species present in solution is also discussed.
This Minireview showcases key advances on the use of polar s‐block organometallic reagents in bioinspired solvents water, glycerol and Deep Eutectic Solvents (DESs), under air, at room temperature and in the presence of moisture, a trio of conditions that for decades has been considered incompatible with the manipulation of these reagents.
The movement of lithium ions into and out of electrodes is central to the operation of lithium-ion batteries. Although this process has been extensively studied at the device level, it remains ...insufficiently characterized at the nanoscale level of grain clusters, single grains and defects. Here, we probe the spatial variation of lithium-ion diffusion times in the battery-cathode material LiCoO(2) at a resolution of ∼100 nm by using an atomic force microscope to both redistribute lithium ions and measure the resulting cathode deformation. The relationship between diffusion and single grains and grain boundaries is observed, revealing that the diffusion coefficient increases for certain grain orientations and single-grain boundaries. This knowledge provides feedback to improve understanding of the nanoscale mechanisms underpinning lithium-ion battery operation.
Complex organic molecules (COMs) are detected in many regions of the interstellar medium, including prestellar cores. However, their formation mechanisms in cold (~10 K) cores remain to this date ...poorly understood. The formyl radical HCO is an important candidate precursor for several O-bearing terrestrial COMs in cores, as an abundant building block of many of these molecules. Several chemical routes have been proposed to account for its formation: on grain surfaces, as an incompletely hydrogenated product of H addition to frozen-out CO molecules; and in the gas phase, either as the product of the reaction between H2CO and a radical or as a product of dissociative recombination of protonated formaldehyde H2COH+. The detection and abundance determination of H2COH+, if present, could provide clues as to whether this latter scenario might apply. We searched for protonated formaldehyde H2COH+ in the prestellar core L1689B using the IRAM 30 m telescope. The H2COH+ ion is unambiguously detected, for the first time, in a cold (~10 K) source. The derived abundance agrees with a scenario in which the formation of H2COH+ results from the protonation of formaldehyde. We use this abundance value to constrain the branching ratio of the dissociative recombination of H2COH+ towards the HCO channel to ~10−30%. This value could however be lower if HCO were efficiently formed from neutral-neutral reactions in the gas phase, and we stress the need for laboratory measurements of the rate constants of these reactions at 10 K. Given the experimental difficulties in measuring branching ratios experimentally, observations can place valuable constraints on these values and provide useful input for chemical networks.
Background
Obesity has been described as a risk factor for COVID‐19 severity and mortality. Previous studies report a linear association between BMI and adverse outcomes, meanwhile in other critical ...illness, excessive fat tissue is related to improved survival. Whether different BMI is related with the survival of patients with severe COVID‐19 deserves further analysis.
Objective
To determine the mortality rate among hospitalized patients with severe COVID‐19 stratified according to BMI.
Methods
The clinical files of all patients hospitalized from March to December 2020 with a positive PCR test for SARS‐CoV‐2 discharged due to improvement or death, were analyzed. A mixed effects logistic regression was carried out to determine which clinical and biochemical characteristics and comorbidities were associated with in‐hospital mortality.
Results
The cohort consisted of 608 patients with a median age of 59 years (interquartile ranges, IQR 46–69 years), median BMI of 28.7 kg/m2 (IQR 25.4–32.4 kg/m2), 65.5% were male. In‐hospital mortality rate was 43.4%. Of the cohort 0.8% had low weight, 20.9% normal weight, 36.0% overweight, 26.5% obesity grade I, 10.2% obesity grade II and 5.6% obesity grade III. Mortality rate was highest in patients with low weight (80%), followed by patients with obesity grade III (58.8%) and grade II (50.0%). Overweight and underweight/obesity grade III were associated with higher mortality (OR of 9.75 1.01–1.10 and OR 4.08 1.64–10.14), after adjusting by sex and age.
Conclusions
The patients in the underweight/overweight and grade 3 obesity categories are at higher risk of COVID‐19 related mortality, compared to those with grade I or II obesity.
•AID-FOREST is a totally automatic software once launched.•AID-FOREST processes very large Lidar point cloud files without any problem.•Artificial intelligence has for the first time been used ...efficiently to detect trees.•Tree detectability was over 97% despite the ecosystem visual complexity.•Diameter at breast height and stem volume estimations were statistically unbiased.
Forest inventories are essential to accurately estimate different dendrometric and forest stand parameters. However, classical forest inventories are time consuming, slow to conduct, sometimes inaccurate and costly. To address this problem, an efficient alternative approach has been sought and designed that will make this type of field work cheaper, faster, more accurate, and easier to complete. The implementation of this concept has required the development of a specifically designed software called “Artificial Intelligence for Digital Forest (AID-FOREST)”, which is able to process point clouds obtained via mobile terrestrial laser scanning (MTLS) and then, to provide an array of multiple useful and accurate dendrometric and forest stand parameters. Singular characteristics of this approach are: No data pre-processing is required either pre-treatment of forest stand; fully automatic process once launched; no limitations by the size of the point cloud file and fast computations.
To validate AID-FOREST, results provided by this software were compared against the obtained from in-situ classical forest inventories. To guaranty the soundness and generality of the comparison, different tree species, plot sizes, and tree densities were measured and analysed. A total of 76 plots (10,887 trees) were selected to conduct both a classic forest inventory reference method and a MTLS (ZEB-HORIZON, Geoslam, ltd.) scanning to obtain point clouds for AID-FOREST processing, known as the MTLS-AIDFOREST method. Thus, we compared the data collected by both methods estimating the average number of trees and diameter at breast height (DBH) for each plot. Moreover, 71 additional individual trees were scanned with MTLS and processed by AID-FOREST and were then felled and divided into logs measuring 1 m in length. This allowed us to accurately measure the DBH, total height, and total volume of the stems.
When we compared the results obtained with each methodology, the mean detectability was 97% and ranged from 81.3 to 100%, with a bias (underestimation by MTLS-AIDFOREST method) in the number of trees per plot of 2.8% and a relative root-mean-square error (RMSE) of 9.2%. Species, plot size, and tree density did not significantly affect detectability. However, this parameter was significantly affected by the ecosystem visual complexity index (EVCI). The average DBH per plot was underestimated (but was not significantly different from 0) by the MTLS-AIDFOREST, with the average bias for pooled data being 1.8% with a RMSE of 7.5%. Similarly, there was no statistically significant differences between the two distribution functions of the DBH at the 95.0% confidence level.
Regarding the individual tree parameters, MTLS-AIDFOREST underestimated DBH by 0.16 % (RMSE = 5.2 %) and overestimated the stem volume (Vt) by 1.37 % (RMSE = 14.3 %, although the BIAS was not statistically significantly different from 0). However, the MTLS-AIDFOREST method overestimated the total height (Ht) of the trees by a mean 1.33 m (5.1 %; relative RMSE = 11.5 %), because of the different height concepts measured by both methodological approaches. Finally, AID-FOREST required 30 to 66 min per ha−1 to fully automatically process the point cloud data from the *.las file corresponding to a given hectare plot. Thus, applying our MTLS-AIDFOREST methodology to make full forest inventories, required a 57.3 % of the time required to perform classical plot forest inventories (excluding the data postprocessing time in the latter case). A free trial of AID-FOREST can be requested at dielmo@dielmo.com.
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