Three six‐coordinate DyIII single‐molecule magnets (SMMs) Dy(OtBu)2(L)4+ with local D4h symmetry are obtained by optimizing the equatorial ligands. One of the compounds with L=4‐phenylpyridine shows ...an energy barrier (Ueff) of 2075(11) K, which is the third largest Ueff, and the first Ueff>2000 K for SMMs with axial‐type symmetry so far. Ab initio analysis indicates that the exceptional uniaxial magnetic anisotropy is deeply related to the axially compressed octahedral geometry. This work provides a new insight into the local D4h symmetry for high‐performance SMMs.
Building single‐molecule magnets: A compressed octahedral dysprosium(III) single‐molecule magnet with local D4h symmetry exhibits an energy barrier over 2000 K.
Circular RNAs (circRNAs), which are single-stranded closed-loop RNA molecules lacking terminal 5' caps and 3' poly(A) tails, are attracting increasing scientific attention for their crucial ...regulatory roles in the occurrence and development of various diseases. With the rapid development of high-throughput sequencing technologies, increasing numbers of differentially expressed circRNAs have been identified in bladder cancer (BCa) via exploration of the expression profiles of BCa and normal tissues and cell lines. CircRNAs are critically involved in BCa biological behaviours, including cell proliferation, tumour growth suppression, cell cycle arrest, apoptosis, invasion, migration, metastasis, angiogenesis, and cisplatin chemoresistance. Most of the studied circRNAs in BCa regulate cancer biological behaviours via miRNA sponging regulatory mechanisms. CircRNAs have been reported to be significantly associated with many clinicopathologic characteristics of BCa, including tumour size, grade, differentiation, and stage; lymph node metastasis; tumour numbers; distant metastasis; invasion; and recurrence. Moreover, circRNA expression levels can be used to predict BCa patients' survival parameters, such as overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS). The abundance, conservation, stability, specificity and detectability of circRNAs render them potential diagnostic and prognostic biomarkers for BCa. Additionally, circRNAs play crucial regulatory roles upstream of various signalling pathways related to BCa carcinogenesis and progression, reflecting their potential as therapeutic targets for BCa. Herein, we briefly summarize the expression profiles, biological functions and mechanisms of circRNAs and the potential clinical applications of these molecules for BCa diagnosis, prognosis, and targeted therapy.
Plants from the genus
have been extensively used in folk medicines to treat diseases such as skin diseases and peptic ulcers and as an antiseptic and analgesic. Most
species, especially
, which is ...used as an expectorant, antiseptic, and analgesic in Chinese traditional medicine, could screen resin after external injury.
is also used in folk medicines in Korea to treat sore throat, bronchitis, cough, expectoration, paralysis, laryngitis, and inflammation. Different parts of various
species can be widely employed for ethnopharmacological applications. Moreover, for ethnopharmacological use, these parts of
species can be applied in combination with other folk medicines.
species consist of versatile natural compounds, with some of them exhibiting particularly excellent pharmacological activities, such as cytotoxic, acetylcholinesterase inhibitory, antioxidant, and antifungal activities. Altogether, these exciting results indicate that a comprehensive review of plants belonging to this genus is essential for helping researchers to continuously conduct an in-depth investigation. In this review, the traditional uses, phytochemistry, corresponding pharmacological activities, and structure-activity relationships of different
species are clarified and critically discussed. More insights into potential opportunities for future research are carefully assessed.
Growing evidences have confirmed the effect of Sacubitril/Valsartan (SV) on antihypertension and cardiac protection in general population. However, there was no prospective study about the effect and ...safety of SV on resistant hypertension and myocardial work in hemodialysis patients. In this single‐center, prospective, before‐after study, enrolled patients were endured with resistant hypertension for more than 6 months. Participants were initially instructed to take SV 50 mg twice daily, and the dosage was gradually increased up to 100 mg twice daily. The primary outcomes were blood pressure (BP) control, N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP), myocardial work (MW), fatigue and life quality. In addition, the adverse events were also recorded in this cohort. A total of 18 patients (34–64 years old) was finally enrolled and completed in this study. The SV‐based regimen provided significantly mean sitting systolic BP (msSBP) and mean sitting diastolic BP (msDBP) reductions from baseline (‐20.7/‐8.3 mm Hg), respectively. The cardiac remodeling parameters were partially improved. Compared to the baseline, NT‐proBNP was significantly reduced at week 4 (8119.50 3710.75, 29300 pg/ml to 7216.50 4124.75, 17455.00 pg/ml, p = .046), which was much lower at week 12 (3130.50 2244.50, 9565.70 pg/ml, p = .037). Global MW index was higher at week 12 compared to the baseline (p = .026). MW efficiency was also improved accordingly compared to the baseline, even though the statistical difference was not significant (p = .226). Life quality and fatigue were improved at week 12 compared to the baseline (all p = .000). There was no serious adverse events were observed. SV safely and effectively controlled resistant hypertension and improved MW as well as life quality in hemodialysis patients.
Rainfall and reservoir water level are commonly regarded as the two major influencing factors for reservoir landslides and are employed for landslide displacement prediction, yet their daily data are ...readily available with current monitoring technology, which makes a more refined analysis possible. However, until now, few efforts have been made to predict landslide displacements using daily data, which is likely to substantially improve accuracy and is crucial for landslide early warning. A novel feature enhancement approach for extracting critical characteristics from daily rainfall and reservoir water level data for use in landslide displacement prediction is proposed in this study. Six models, including gated recurrent units (GRUs), long short-term memory (LSTM), and support vector regression (SVR) with an unenhanced dataset and GRU-E, LSTM-E, and SVR-E with an enhanced dataset, were employed for displacement predictions at four GPS monitoring stations on the Baijiabao landslide, a typical step-like reservoir landslide. The results show that the accuracy values of all the enhanced models were significantly improved, and the GRU-E model achieved the most significant improvement, with the RMSE decreasing by 24.39% and R2 increasing by 0.2693, followed by the LSTM-E and SVR-E models. Further, the GRU-E model consistently outperformed the other models, achieving the highest R2 of 0.6265 and the lowest RMSE of 16.5208 mm, significantly superior than the others. This study indicates the feasibility of improving the accuracy of landslide monthly displacement predictions with finer monitoring data and provides valuable insights for future research.
Three six-coordinate Dy
single-molecule magnets (SMMs) Dy(O
Bu)
(L)
with local D
symmetry are obtained by optimizing the equatorial ligands. One of the compounds with L=4-phenylpyridine shows an ...energy barrier (U
) of 2075(11) K, which is the third largest U
, and the first U
>2000 K for SMMs with axial-type symmetry so far. Ab initio analysis indicates that the exceptional uniaxial magnetic anisotropy is deeply related to the axially compressed octahedral geometry. This work provides a new insight into the local D
symmetry for high-performance SMMs.
Purpose
To study the effects of magnetization transfer (MT, in which a semi‐solid spin pool interacts with the free pool), in the context of magnetic resonance fingerprinting (MRF).
Methods
...Simulations and phantom experiments were performed to study the impact of MT on the MRF signal and its potential influence on T1 and T2 estimation. Subsequently, an MRF sequence implementing off‐resonance MT pulses and a dictionary with an MT dimension, generated by incorporating a two‐pool model, were used to estimate the fractional pool size in addition to the B1+, T1, and T2 values. The proposed method was evaluated in the human brain.
Results
Simulations and phantom experiments showed that an MRF signal obtained from a cross‐linked bovine serum sample is influenced by MT. Using a dictionary based on an MT model, a better match between simulations and acquired MR signals can be obtained (NRMSE 1.3% vs. 4.7%). Adding off‐resonance MT pulses can improve the differentiation of MT from T1 and T2. In vivo results showed that MT affects the MRF signals from white matter (fractional pool‐size ~16%) and gray matter (fractional pool‐size ~10%). Furthermore, longer T1 (~1060 ms vs. ~860 ms) and T2 values (~47 ms vs. ~35 ms) can be observed in white matter if MT is accounted for.
Conclusion
Our experiments demonstrated a potential influence of MT on the quantification of T1 and T2 with MRF. A model that encompasses MT effects can improve the accuracy of estimated relaxation parameters and allows quantification of the fractional pool size.
A landslide susceptibility model based on a metaheuristic optimization algorithm (germinal center optimization (GCO)) and support vector classification (SVC) is proposed and applied to landslide ...susceptibility mapping in the Three Gorges Reservoir area in this paper. The proposed GCO-SVC model was constructed via the following steps: First, data on 11 influencing factors and 292 landslide polygons were collected to establish the spatial database. Then, after the influencing factors were subjected to multicollinearity analysis, the data were randomly divided into training and testing sets at a ratio of 7:3. Next, the SVC model with 5-fold cross-validation was optimized by hyperparameter space search using GCO to obtain the optimal hyperparameters, and then the best model was constructed based on the optimal hyperparameters and training set. Finally, the best model acquired by GCO-SVC was applied for landslide susceptibility mapping (LSM), and its performance was compared with that of 6 popular models. The proposed GCO-SVC model achieved better performance (0.9425) than the genetic algorithm support vector classification (GA-SVC; 0.9371), grid search optimized support vector classification (GRID-SVC; 0.9198), random forest (RF; 0.9085), artificial neural network (ANN; 0.9075), K-nearest neighbor (KNN; 0.8976), and decision tree (DT; 0.8914) models in terms of the area under the receiver operating characteristic curve (AUC), and the trends of the other metrics were consistent with that of the AUC. Therefore, the proposed GCO-SVC model has some advantages in LSM and may be worth promoting for wide use.
Accurately predicting the surface displacement of the landslide is important and necessary. However, most of the existing research has ignored the frequency component of inducing factors and how it ...affects the landslide deformation. Therefore, a hybrid displacement prediction model based on time series theory and various intelligent algorithms was proposed in this paper to study the effect of frequency components. Firstly, the monitoring displacement of landslide from the Three Gorges Reservoir area (TGRA) was decomposed into the trend and periodic components by complete ensemble empirical mode decomposition (CEEMD). The trend component can be predicted by the least square method. Then, time series of inducing factors like rainfall and reservoir level was reconstructed into high frequency components and low frequency components with CEEMD and t-test, respectively. The dominant factors were selected by the method of dynamic time warping (DTW) from the frequency components and other common factors (e.g., current monthly rainfall). Finally, the ant colony optimization-based support vector machine regression (ACO-SVR) is utilized for prediction purposes in the TGRA. The results demonstrate that after considering the frequency components of landslide-induced factors, the accuracy of the displacement prediction model based on ACO-SVR is better than that of other models based on SVR and GA-SVR.
In this article, ABA triblock copolymer (tri-BCP) thermoplastic elastomers with poly(ethylene oxide) (PEO) middle block and polyzwitterionic poly(4-vinylpyridine) propane-1-sulfonate (PVPS) outer ...blocks were synthesized. The PVPS
PEO
PVPS tri-BCPs were doped with lithium bis-(trifluoromethane-sulfonyl) imide (LiTFSI) and used as solid polyelectrolytes (SPEs). The thermal properties and microphase separation behavior of the tri-BCP/LiTFSI hybrids were studied. Small-angle X-ray scattering (SAXS) results revealed that all tri-BCPs formed asymmetric lamellar structures in the range of PVPS volume fractions from 12.9% to 26.1%. The microphase separation strength was enhanced with increasing the PVPS fraction (
) but was weakened as the doping ratio increased, which affected the thermal properties of the hybrids, such as melting temperature and glass transition temperature, to some extent. As compared with the PEO/LiTFSI hybrids, the PVPS
PEO
PVPS/LiTFSI hybrids could achieve both higher modulus and higher ionic conductivity, which were attributed to the physical crosslinking and the assistance in dissociation of Li
ions by the PVPS blocks, respectively. On the basis of excellent electrical and mechanical performances, the PVPS
PEO
PVPS/LiTFSI hybrids can potentially be used as solid electrolytes in lithium-ion batteries.
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