Currently, discovering new materials with superior second-order nonlinear optical (NLO) performance has become a very hot research topic in the fields of chemistry and materials science. Now, density ...functional theory (DFT) has become a powerful tool to predict the performance of novel materials. In this paper, based on benzannulated and selenophene-annulated expanded helicenes, twenty-six helicenes are designed by introduction donor/acceptor moieties and their combinations at different substituent positions. The geometrical/electronic structures, electronic transition, and second-order NLO properties of these helicenes are full investigated by DFT/TDDFT theory. The investigations show that these helicenes have large first hyperpolarizability values (
β
HRS
). For instance, the
β
HRS
value (29.95 × 10
−30
esu) of helicene
H24
is about 7 times larger than that of the highly π-delocalized phenyliminomethyl ferrocene complex. In addition, the introduction of acceptor NO
2
unit at R
7
and R
8
positions for helicenes
H1
and
H15
can obtain the largest
β
HRS
value, which is attributed to the enhancement of electron acceptor ability. In view of large NLO response and intrinsic asymmetric structures, the studied helicenes have the possibility to be excellent second-order NLO materials.
The nonlinear optical properties of the studied helicenes were studied with the aid of the DFT calculations.
Morphology transformation and crystal growth strategies of metal oxide semiconductors are still extensively studied in material science recently, because the morphology and crystallinity ...significantly affect the physicochemical characteristics of metal oxide nanomaterials. However, understanding the morphology changes of
α
-MoO
3
induced by annealing is still a challenge. Herein, the nanostructure transition of
α
-MoO
3
induced by the annealing temperature is carefully investigated via the XRD and SEM methods. It can be found that crystallization is highly dependent on the annealing temperature. Interestingly, the MoO
3
nanoflowers can change into nanosheets at 500 °C. Afterward, the nanosheets turned into microrods with the increase in annealing temperature due to the continuous growth of MoO
3
crystal. On the other hand, the sensing performances of various MoO
3
nanostructures are studied toward ethanol gas. Compared to the MoO
3
nanoflowers and microrods, the MoO
3
nanosheets-based sensor exhibits superior sensing performance to ethanol, and the maximum response value is 8.06.
Copper (Cu), with the advantage of producing a deep reduction product, is a unique catalyst for the electrochemical reduction of CO2 (CO2RR). Designing a Cu-based catalyst to trigger CO2RR to a ...multicarbon product and understanding the accurate structure–activity relationship for elucidating reaction mechanisms still remain a challenge. Herein, we demonstrate a rational design of a core–shell structured silica-copper catalyst (p-Cu@m-SiO2) through Cu–Si direct bonding for efficient and selective CO2RR. The Cu–Si interface fulfills the inversion in CO2RR product selectivity. The product ratio of C2H4/CH4 changes from 0.6 to 14.4 after silica modification, and the current density reaches a high of up to 450 mA cm–2. The kinetic isotopic effect, in situ attenuated total reflection Fourier-transform infrared spectra, and density functional theory were applied to elucidate the reaction mechanism. The SiO2 shell stabilizes the *H intermediate by forming Si–O–H and inhibits the hydrogen evolution reaction effectively. Moreover, the direct-bonded Cu–Si interface makes bare Cu sites with larger charge density. Such bare Cu sites and Si–O–H sites stabilized the *CHO and activated the *CO, promoting the coupling of *CHO and *CO intermediates to form C2H4. This work provides a promising strategy for designing Cu-based catalysts with high C2H4 catalytic activity.
In addition to causing the pandemic influenza outbreaks of 1918 and 2009, subtype H1N1 influenza A viruses (IAVs) have caused seasonal epidemics since 1977. Antigenic property of influenza viruses ...are determined by both protein sequence and N-linked glycosylation of influenza glycoproteins, especially hemagglutinin (HA). The currently available computational methods are only considered features in protein sequence but not N-linked glycosylation.
A multi-task learning sparse group least absolute shrinkage and selection operator (LASSO) (MTL-SGL) regression method was developed and applied to derive two types of predominant features including protein sequence and N-linked glycosylation in hemagglutinin (HA) affecting variations in serologic data for human and swine H1N1 IAVs. Results suggested that mutations and changes in N-linked glycosylation sites are associated with the rise of antigenic variants of H1N1 IAVs. Furthermore, the implicated mutations are predominantly located at five reported antibody-binding sites, and within or close to the HA receptor binding site. All of the three N-linked glycosylation sites (i.e. sequons NCSV at HA 54, NHTV at HA 125, and NLSK at HA 160) identified by MTL-SGL to determine antigenic changes were experimentally validated in the H1N1 antigenic variants using mass spectrometry analyses. Compared with conventional sparse learning methods, MTL-SGL achieved a lower prediction error and higher accuracy, indicating that grouped features and MTL in the MTL-SGL method are not only able to handle serologic data generated from multiple reagents, supplies, and protocols, but also perform better in genetic sequence-based antigenic quantification.
In summary, the results of this study suggest that mutations and variations in N-glycosylation in HA caused antigenic variations in H1N1 IAVs and that the sequence-based antigenicity predictive model will be useful in understanding antigenic evolution of IAVs.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract Pancreatic cancer is a devastating disease with a dismal prognosis. Surgical resection is the only curative option but is heavily hampered by delayed diagnosis. Due to few therapeutic ...treatments available, novel and efficacious therapy is urgently needed. Histone deacetylase inhibitors (HDACIs) are emerging as a prominent class of therapeutic agents for pancreatic cancer and have exhibited significant anticancer potential with negligible toxicity in preclinical studies. Clinical evaluations of HDACIs are currently underway. HDACIs as monotherapy in solid tumors have proven less effective than hematological malignancies, the combination of HDACIs with other anticancer agents have been assessed for advanced pancreatic cancer. In this review, we describe the molecular mechanism underpin the anticancer effect of HDACIs in pancreatic cancer and summarize the recent advances in the rationale for the combination strategies incorporating HDACIs. In addition, we discuss the importance of identifying predictors of response to HDACI-based therapy.
Bisected N -glycans represent a unique class of protein N -glycans that play critical roles in many biological processes. Herein, we describe the systematic synthesis of these structures. A bisected ...N -glycan hexasaccharide was chemically assembled with two orthogonal protecting groups attached at the C2 of the branching mannose residues, followed by sequential installation of GlcNAc and LacNAc building blocks to afford two asymmetric bisecting “cores”. Subsequent enzymatic modular extension of the “cores” yielded a comprehensive library of biantennary N -glycans containing the bisecting GlcNAc and presenting 6 common glycan determinants in a combinatorial fashion. These bisected N -glycans and their non-bisected counterparts were used to construct a distinctive glycan microarray to study their recognition by a wide variety of glycan-binding proteins (GBPs), including plant lectins, animal lectins, and influenza A virus hemagglutinins. Significantly, the bisecting GlcNAc could bestow (PHA-L, rDCIR2), enhance (PHA-E), or abolish (ConA, GNL, anti-CD15s antibody, etc. ) N -glycan recognition of specific GBPs, and is tolerated by many others. In summary, synthesized compounds and the unique glycan microarray provide ideal standards and tools for glycoanalysis and functional glycomic studies. The microarray data provide new information regarding the fine details of N -glycan recognition by GBPs, and in turn improve their applications.
In this study, we developed two new SIMS (secondary ion mass spectrometry) analytical protocols to simultaneously measure oxygen-hydrogen (O-H) isotopic compositions and water content for hydrous ...geological samples. These two protocols involve the measurement of two sets of secondary ion contents: (1)
1
H,
2
H,
16
O,
18
O; and (2)
16
O,
16
O
1
H,
18
O,
17
O
1
H,
16
O
2
H. Both measurements utilize a hybrid dynamic multi-collector system of CAMECA IMS 1280-HR, which benefits from both the static multi-collector mode and peak-hopping mono-collector mode. These new methods can simultaneously measure (with high-precision) the
18
O/
16
O ratio in static multi-collector mode without trading off its analytical precision, and
1
H/
16
O (or
16
O
1
H/
16
O) and
2
H/
1
H (or
16
O
2
H/
16
O
1
H) ratios in conventional peak-hopping mono-collector mode. Three glass samples (LBS7H, LBS5H and LBS6H-) with known water contents and two apatite samples (Kovdor, Durango) with known oxygen-hydrogen isotopes and water content were measured to verify the protocols' reliability. The olivine crystal San Carlos with ∼1 ppmw water content was used for background monitoring. For the apatite samples, the external precision (spot-to-spot reproducibility) for δ
18
O and δD is better than 0.56‰ (2SD) and 54‰ (2SD), respectively. After eliminating the outlier (beyond 3SD error), the external precision of
16
O
1
H/
16
O or
1
H/
16
O ratio improves to 10.27% (2SD). For the glass samples, the water content calibration curves, which were constructed by comparison of the known water content with the SIMS measured
16
O
1
H/
16
O or
1
H/
16
O ratios, yielded good correlations. It is noteworthy that the apatite and glass samples can have a uniform water content calibration curve for protocol 1, but not for protocol 2, indicating different matrix effects for the two protocols.
In this study, we developed two new SIMS (secondary ion mass spectrometry) analytical protocols to simultaneously measure oxygen-hydrogen (O-H) isotopic compositions and water content for hydrous geological samples.
The electroencephalogram (EEG), for measuring the electrophysiological activity of the brain, has been widely applied in automatic detection of epilepsy seizures. Various EEG-based seizure detection ...algorithms have already yielded high sensitivity, but training those algorithms requires a large amount of labelled data. Data labelling is often done with a lot of human efforts, which is very time-consuming. In this study, we propose a hybrid system integrating an unsupervised learning (UL) module and a supervised learning (SL) module, where the UL module can significantly reduce the workload of data labelling. For preliminary seizure screening, UL synthesizes amplitude-integrated EEG (aEEG) extraction, isolation forest-based anomaly detection, adaptive segmentation, and silhouette coefficient-based anomaly detection evaluation. The UL module serves to quickly locate the determinate subjects (seizure segments and seizure-free segments) and the indeterminate subjects (potential seizure candidates). Afterwards, more robust seizure detection for the indeterminate subjects is performed by the SL using an EasyEnsemble algorithm. EasyEnsemble, as a class-imbalance learning method, can potentially decrease the generalization error of the seizure-free segments. The proposed method can significantly reduce the workload of data labelling while guaranteeing satisfactory performance. The proposed seizure detection system is evaluated using the Children's Hospital Boston - Massachusetts Institute of Technology (CHB-MIT) scalp EEG dataset, and it achieves a mean accuracy of 92.62%, a mean sensitivity of 95.55%, and a mean specificity of 92.57%. To the best of our knowledge, this is the first epilepsy seizure detection study employing the integration of both the UL and the SL modules, achieving a competitive performance superior or similar to that of the state-of-the-art methods.
Abstract
The recovery of low-quality waste heat is a major problem in energy utilization. In order to solve this problem and improve energy utilization, the research group designed a low-quality ...waste heat power generation device with Roots power machine as the core. However, the device has poor ability to adjust the rotation speed and it is difficult to generate electricity stably. The fundamental reason is that the system has many variables and strong coupling. According to the actual working conditions, the power of the device is 10 kW, and the fluctuation range should be within ± 7%. On the one hand, it can be improved by hardware, on the other hand, the design of software is also very critical. At present, through the investigation of domestic and foreign researches on the control system, it is found that the stability of the system is gradually improved, but the problem of strong coupling between variables has not been effectively solved. Therefore, the research group modeled the variables in the system and obtained a coupled model. Based on the couple model, the research group introduced nonlinear multi-model adaptive closed-loop decoupling control and designed a control system. The simulation results show that the maximum overshoot of the control system is 3.9%, the adjustment time is also reduced, and it is stable in low quality waste heat recovery device. Experimental results show that under the control of the system, the rotational speed of roots motor can keep stable, the maximum deviation is not more than 21.4 r/min, and the fluctuation range is within ± 7%, which meets the requirements of the index. This has laid the foundation for the follow-up research of grid-connected power generation.
Detecting the characteristic decomposition products (SO2, SOF2, and HF) of SF6 is an effective way to diagnose the electric discharge in SF6-insulated equipment. Based on first-principles ...calculations, Au, Ag, and Cu were chosen as the surface modification transition metal to improve the adsorption and gas-sensing properties of MoTe2 monolayer towards SO2, SOF2, and HF gases. The results show that Au, Ag, and Cu atoms tend to be trapped by TH sites on the MoTe2 monolayer, and the binding strength increases in the order of Ag < Au < Cu. In gas adsorption, the moderate adsorption energy provides the basis that the TM-MoTe2 monolayer can be used as gas-sensing material for SO2, SOF2, and HF. The conductivity of the adsorption system changes significantly. The conductivity decreases upon gases adsorption on TM-MoTe2 monolayer, except the conductivity of Ag-MoTe2 monolayer increases after interacting with SOF2 gas.
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