Search

Objective: This study aimed to investigate the characteristics of blood lipid metabolism in twin pregnancy and its combined with gestational diabetes mellitus (GDM) or pregnancy-induced hypertension (PIH). Methods: This study retrospectively analyzed 96 cases of twin pregnancy and 232 cases of full-term singleton pregnancy, and they were filed in our hospital, undergone antenatal examination and gave birth from March 2016 to March 2021. Among 96 cases of twin pregnancy, 22 cases had GDM, and 18 cases had gestational hypertension. Comparison of general data and blood lipid levels, including triglyceride (TG) and total cholesterol (TC), between twin pregnancy and singleton pregnancy was performed. Comparison of blood lipid levels between GDM group and non-GDM group in twin pregnancy was performed. Comparison of blood lipid levels between the PIH group and the non-PIH group in twin pregnancy was performed. Results For the twin pregnancy, the TG level in the third trimester was higher than that in the second and first trimester, and the TG level in the second trimester was higher than that in the first trimester (P 0.05). The TG level of twin pregnancy was higher than that of singleton pregnancy in the first, second and third trimesters (P 0.05). For the twin pregnancy, the TG level in the GDM group was higher than that in the non-GDM group (P 0.05). The TG level in the first, second and third trimester of twin pregnancy combined with PIH group was higher than that in the non-hypertensive group (P 0.05). Conclusions The lipid levels in twin pregnancy increased with the increase of gestational age, and the TG level in twin pregnancy complicated with GDM or PIH was higher than that in twin pregnancy without with GDM or PIH, indicating that the blood lipid metabolism was related to the occurrence of GDM and PIH in twin pregnancy to some extent.

Low-dimensional materials have excellent properties which are closely related to their dimensionality. However, the growth mechanism underlying tunable dimensionality from 2D triangles to ID ribbons of such materials is still unrevealed. Here, we establish a general kinetic Monte Carlo model for transition metal dichalcogenides (TMDs) growth to address such an issue. Our model is able to reproduce several key ñndings in experiments, and reveals that the dimensionality is determined by the lattice mismatch and the interaction strength between TMDs and the substrate. We predict that the dimensionality can be well tuned by the interaction strength and the geometry of the substrate. Our work deepens the understanding of tunable dimensionality of low-dimensional materials and may inspire new concepts for the design of such materials with expected dimensionality.

When an infectious disease recurs, it may be due to treatment failure or a new infection. Being able to distinguish and classify these two different outcomes is critical in effective disease control. A multi-state model based on Markov processes is a typical approach to estimating the transition probability between the disease states. However, it can perform poorly when the disease state is unknown. This article aims to demonstrate that the transition likelihoods of baseline covariates can distinguish one cause from another with high accuracy in infectious diseases such as malaria. A more general model for disease progression can be constructed to allow for additional disease outcomes. We start from a multinomial logit model to estimate the disease transition probabilities and then utilize the baseline covariate's transition information to provide a more accurate classification result. We apply the expectation-maximization (EM) algorithm to estimate unknown parameters, including the marginal probabilities of disease outcomes. A simulation study comparing our classifier to the existing two-stage method shows that our classifier has better accuracy, especially when the sample size is small. The proposed method is applied to determining relapse vs reinfection outcomes in two Plasmodium vivax treatment studies from Cambodia that used different genotyping approaches to demonstrate its practical use.

Perspective on This Article from Loss of Heterozygosity (LOH) Profiles—Validated Risk Predictors for Progression to Oral Cancer

Unravelling the complex kinetics of electrocatalysis is essential for the design of electrocatalysts with high performance. Mass transfer and electron transfer are two primary factors that need to be optimized in order to enhance electrocatalytic reactions. The use of nanocatalysts proves to be a promising way of promoting the performance of electrocatalytic reactions, this improvement is usually attributed to their ability to enhance electron transfer. However, when catalysts are taken down to the nanoscale, their size is comparable to the thickness of an electrical double layer, so any curvature can lead to an inhomogeneous local electric field on the electrode, which then changes the mass transfer essentially. In this article, we introduce the new concept of local-field-induced mass transfer in nano-electrocatalytic systems, and provide a brief review of recent progress, revealing its effect on nano-electrocatalysis, which may bring new insight into the future design of nano-electrocatalysts.

The kinetics of electrode reactions including mass transfer and surface reaction is essential in electrocatalysis, as it strongly determines the apparent reaction rates, especially on nanostructured electrocatalysts. However, important challenges still remain in optimizing the kinetics of given catalysts with suitable constituents, morphology, and crystalline design to maximize the electrocatalytic performances. We propose a comprehensive kinetic model coupling mass transfer and surface reaction on the nanocatalyst-modified electrode surface to explore and shed light on the kinetic optimization in electrocatalysis. Moreover, a theory-guided microchemical engineering (MCE) strategy has been demonstrated to rationally redesign the catalysts with optimized kinetics. Experimental measurements for methanol oxidation reaction in a 3D ordered channel with tunable channel sizes confirm the calculation prediction. Under the optimized channel size, mass transfer and surface reaction in the channeled microreactor are both well regulated. This MCE strategy will bring about a significant leap forward in structured catalyst design and kinetic modulation.

Burn injury has posed devastating burdens on the public health due to its inevitable damage to the skin structure resulting in the increased risk of infection. Therefore, it is highly demanding to develop efficacious antibacterial wound-healing dressing. Despite the favourable wound-healing activities, the curative efficacy of phytochemical compounds of quercetin (Qe) and its derivatives is limited by their poor water solubility. Here, we have fabricated a novel electrospun nanofiber membrane (ENM) consisting of polycaprolactone (PCL), chitosan oligosaccharides (COS), and Qe/Rutin (Ru) as the potential bioactive dressing for wound healing. The incorporation of chitosan oligosaccharides (COSs) in the PCL scaffold at the optimized molar ratio not only contributed to the improved hydrophilicity and water absorption performance of the ENM but effectively increased the specific surface area of the formed nanofibers. In particular, the antioxidant and antibacterial activities of the Qe/rutin-loaded nanofiber membranes were tested, which revealed that the PCL-COS-Qe membrane exhibited superior performance among all nanofiber membranes. Therefore, the developed PCL-COS-Qe/Ru nanofiber membranes hold enormous potential as healthcare products, such as wound dressings for burn injuries.

High roughness has been proved to be an effective design strategy for electrocatalyst in many systems. Especially, high selectivity of carbon monoxide reduction (CORR) in competition with the hydrogen evolution reaction has been observed on high roughness electrocatalysts. However, the two well-known mechanisms, i.e., decreasing the energy barrier of CORR and increasing local pH, failed to understand the roughness-enhanced selectivity in a recent experiment. Herein we unravel the hidden mechanism by establishing a comprehensive kinetic model for CORR on catalysts with different roughness factors. We conclude that the roughness-enhanced CORR selectivity is actually kinetic controlled by local-electric-field-directed mass transfer of adsorbed species on the electrode surface. Several ways to optimize CORR selectivity are predicted. Our work highlights the kinetics in electrocatalysis on nanocatalysts, and provides a conceptually new principle for future catalyst design.

Diffusion of tracer particles in active bath has attracted extensive attention in recent years. So far, most studies have considered isotropic spherical tracer particles, while the diffusion of anisotropic particles has rarely been involved. Here we investigate the diffusion dynamics of a rigid rod tracer in a bath of active particles by using Langevin dynamics simulations in a two-dimensional space. Particular attention is paid to how the translation (rotation) diffusion coefficient \begin{document}$ D_{ \rm{T}} $\end{document} ( \begin{document}$ D_{ \rm{R}} $\end{document} ) change with the length of rod \begin{document}$ L $\end{document} and active strength \begin{document}$ F_{ \rm{a}} $\end{document} . In all cases, we find that rod exhibits superdiffusion behavior in a short time scale and returns to normal diffusion in the long time limit. Both \begin{document}$ D_{ \rm{T}} $\end{document} and \begin{document}$ D_{ \rm{R}} $\end{document} increase with \begin{document}$ F_{ \rm{a}} $\end{document} , but interestingly, a nonmonotonic dependence of \begin{document}$ D_{ \rm{T}} $\end{document} ( \begin{document}$ D_{ \rm{R}} $\end{document} ) on the rod length has been observed. We have also studied the translation-rotation coupling of rod, and interestingly, a negative translation-rotation coupling is observed, indicating that rod diffuses more slowly in the parallel direction compared to that in the perpendicular direction, a counterintuitive phenomenon that would not exist in an equilibrium counterpart system. Moreover, this anomalous (diffusion) behavior is reentrant with the increase of \begin{document}$ F_{ \rm{a}} $\end{document} , suggesting two competitive roles played by the active feature of bath particles.

Nowadays, pathogenic infection has posed a severe threat to the public health and environmental sanitation, urging a continuous search of efficacious and safe bactericidal agents of various formulated forms. Here, a facile one-pot hydrothermal preparation of mesoporous silica nanoparticles using ultrasonication-assisted nanoemulsion of α-Linolenic acid (α-LA) as template was developed. The formed silica mesocomposite at water/fatty-acid surface provides an easy yet green synthesis route, which can be generalized for the further encapsulation of hydrophobic drugs such as antimycobacterial Rifampicin (RIF). The obtained α-LA nanoemulsion-templated silica nanoparticles (LNS NPs), with a weight content of ∼17% α-LA in the composite, showed apparent antibacterial effect against Staphylococcus aureus (S. aureus). By comparison, the removal of α-LA from the silica nanoparticles (LNS-1 NPs) resulted in the composite of enlarged pore size with negligible bactericidal activities. Notably, the Isoniazide (INH) and Rifampicin (RIF)-encapsulated LNS NPs exhibited outstanding antimycobacterial activity against both drug-sensitive and drug-resistant Mycobacterium tuberculosis (M. tuberculosis). The obtained highly biocompatible, biosafe and low-energy consumptive α-LA-contained mesostructured silica-based bactericide holds promising therapeutic potentials to tackle the emerging drug-resistant infectious microbes.

Light utilization largely governs the performance of CO

Infectious microbes that spread easily in healthcare facilities remain as the severe threat for the public health, especially among immunocompromised populations. Given the intricate problem of dramatic increase in resistance to common biocides, the development of safe and efficient biocide formulated agents to alleviate drug resistance is highly demanding. In this study, Schiff-base ligands were successfully formed on natural biopolymer of epsilon-poly-L-lysine (e-PL) decorated aldehyde functionalized mesoporous silica SBA-15 (CHO-SBA-15) for the selective coordination of silver ions, which was affirmed by various physicochemical methods. Besides the identified broad-spectrum antibacterial activities, the as-prepared Schiff-base silver nanocomplex (CHO-SBA-15/e-PL/Ag, CLA-1) exhibited an improved inhibitory effect on infectious pathogen growth typified by Escherichia coli and Staphylococcus aureus in comparison with two control silver complexes without Schiff-base conjugates, SBA-15/e-PL/Ag and CHO-SBA-15/Ag, respectively. In addition, CLA-1 remarkably inhibited the growth of Mycobacterium tuberculosis due to the excellent antimicrobial activity of silver species. Significantly, CLA-1 kills Candida albicans cells, inhibits biofilm formation, and eliminates preformed biofilms, with no development of resistance during continuous serial passaging. The antifungal activity is connected to disruption of bacterial cell membranes and increased levels of intracellular reactive oxygen species. In mouse models of multidrug-resistant C. albicans infection, CLA-1 exhibited efficient in vivo fungicidal efficacy superior to two antifungal drugs, amphotericin B and fluconazole. Moreover, CLA-1 treatment induces negligible toxicity against normal tissues with safety. Therefore, this study reveals the pivotal role of the molecular design of Schiff-base silver nanocomplex formation on biopolymer surface-functionalized silica mesopores as a green and efficient nanoplatform to tackle infectious microbes.

Although synthetic ZnO nanoparticles (Nano-ZnO) as an alternative of ZnO compounds have been extensively used such as in livestock production, the increased consuming of Nano-ZnO has raised considerable concerns in environmental pollution and public health. Because of the low digestion of Nano-ZnO, the systematic studies on their interactions with gut microbiota remain to be clarified.Nano-ZnOs were prepared by co-precipitation (ZnO-cp) and high temperature thermal decomposition (ZnO-td) as well as the commercial type (ZnO-s). Transmission electron microscopy (TEM) was used to monitor the morphology of Nano-ZnO. CCK-8 assay was used for cytotoxicity evaluation. Total antioxidant capacity assay, total superoxide dismutase assay, and lipid peroxidation assay were used to evaluate oxidative states of rats. 16S rRNA was used to study the impact of Nano-ZnO on the rat gut microbiome.Both ZnO-cp and ZnO-td exhibited low cytotoxicity while ZnO-s and ZnO-td exhibited prominent antibacterial activities. After a 28-day oral feeding with 1000 mg/kg Zn at dietary dosage, ZnO-s showed slight effect on causing oxidative stress in comparison with that of ZnO-cp and ZnO-td. Results of 16S rRNA sequencing analysis indicated that ZnO-td as a promising short-term nano-supplement can increase probiotics abundances like strains belonged to the genus Lactobacillus and provide the antipathogenic effect.The results of the gut microbiome alteration by synthetic Nano-ZnO not only provide solution to exposure monitoring of environmental hazard, but rationalize their large-scale manufacture as alternative additive in the food chain.

From the organization of animal flocks to the emergence of swarming behaviors in bacterial suspension, populations of motile organisms at all scales display coherent collective motion. Recent studies showed that the anisotropic interaction between active particles plays a key role in the phase behaviors. Here we investigate the collective behaviors of based-active Janus particles that experience an anisotropic interaction of which the orientation is opposite to the direction of active force by using Langevin dynamics simulations in two dimensional space. Interestingly, the system shows emergence of collective swarming states upon increasing the total area fraction of particles, which is not observed in systems without anisotropic interaction or activity. The threshold for emergence of swarming states decreases as particle activity or interaction strength increases. We have also performed basic kinetic analysis to reproduce the essential features of the simulation results. Our results demonstrate that anisotropic interactions at the individual level are sufficient to set homogeneous active particles into stable directed motion.

Multifunctional catalysts with distinct functional components are known to have much improved selectivity. However, the well-known proximity-dependent selectivity observed in several high profile experiments is yet to be understood. Here, we reveal that such dependence is closely associated with the kinetics involved. Based on reaction-diffusion dynamics together with kinetic Monte Carlo simulation on a coarse-grained model, one famous example of bifunctional catalysis, namely the proximity-dependent selectivity from carbon dioxide to liquid fuels on a bifunctional catalyst composed of HZSM-5 and In2O3, has been systematically examined. It is found that the diffusion kinetics of the intermediate methanol generated on In2O3 plays a decisive role for the selectively. For different In2O3/HZSM-5 proximities, the local methanol concentration induce a shift of the dominant process for subsequent methanol-to-hydrocarbon reactions inside HZSM-5, resulting in a preferred reaction window to generate favorable liquid fuels with profound high selectivity. Our findings emphasize the importance of the largely overlooked kinetic in the design of multifunctional catalysts.

Objective To investigate clinical values of early-pregnancy (8–13 weeks) glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), and body mass index (BMI) in screening gestational diabetes mellitus (GDM). Methods A total of 1120 cases underwent a 75 g oral glucose tolerance test (OGTT), of which 216 cases with GDM were selected as the study group, and 278 cases without GDM were selected as the control group. FPG, HbA1c, and BMI in early pregnancy were measured. The correlation between FPG, HbA1c and BMI in early pregnancy and the incidence of GDM was analyzed by binary logistic regression, and the value of each index in predicting GDM alone or in combination was evaluated. Results FPG, HbA1c, and BMI in early pregnancy in the GDM group were higher than those in the control group, and the differences were statistically significant (P < .05). Binary logistic regression analysis showed that FPG, HbA1c, and BMI were risk factors for GDM in early pregnancy (odds ratio [OR] values were 3.374 [P < .05], 4.644 [P < .001], and 1.077 [P < .001], respectively). The area under the receiver operating characteristic (ROC) curve of FPG, glycated hemoglobin, and BMI in screening GDM for early pregnancy were 0.647, 0.661, and 0.608, respectively, while the area under the ROC curve of the combination of these 3 indicators was 0.736. Conclusion We found that FPG, HbA1c, and BMI in early pregnancy might be the potential risk factors for the occurrence of GDM, and the combination of them had certain clinical predictive value for GDM. However, it is still necessary for more studies, especially prospective studies, to validate our findings in the future.

Developing efficient charge separation strategies is essential to achieve high-power conversion efficiency in the fields of chemistry, biology, and material science. Herein, we develop a facile strategy for fabrication of unique wafer-scale radial nanowire assemblies by exploiting shear force in rotary solution. The assembly mechanism can be well revealed by the large-scale stochastic dynamics simulation. Free electrons can be rapidly generated to produce quantitatively tunable current output when the radial nanowire assemblies rotate under the magnetic field. Moreover, the photoconductive performance of the radial semiconductor nanowire assemblies can be remarkably enhanced as the electron-hole recombination was retrained by the efficient charge separation under the rotating magnetic field. Such large-scale unique nanowire assemblies will facilitate the design of an efficient charge separation process in biosystem, sensors, and photocatalysis.

The {[Sm2(FDC)2](FDC) · 10H2O}n complex, where H2FDC is a 2,5-furandicarboxylic acid, has been prepared by hydrothermal reaction and structurally characterized by X-ray single-crystal diffraction and elemental analyses. In the complex, each Sm3+ ion is nine-coordinated by four O atoms from two H2FDC ligands and five O atoms from five water molecules. Due to the crucial role of oxalate detection in food chemistry and clinical analysis, oxalate detecting properties were investigated in water by ultraviolet and visible spectroscopy. The results indicated that the complex is a potential candidate for oxalate detector in aqueous solution.