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Objective: To screen lactic acid bacteria strains with strong ability to produce extracellular polysaccharide. Methods: Forty strains of lactic acid bacteria isolated and preserved in the laboratory were selected, and the commercial strain L. rhamnosus GG （LGG） was used as the positive control strain. The strains with high extracellular polysaccharide yield were screened by colony drawing method and phenol-sulfuric acid method, and their stress resistance, safety and antibiotic sensitivity were tested in vitro. The phenotypic characteristics and species identification of the finally obtained strains were analyzed. Results: After primary screening and secondary screening of 40 strains of lactic acid bacteria, 10 strains of lactic acid bacteria with high extracellular polysaccharide production were obtained. After comprehensive evaluation of polysaccharide production, stress resistance and preliminary safety of the 10 strains of lactic acid bacteria, 4 strains of lactic acid bacteria with high EPS production were finally isolated and identified, namely, 2 strains of lactobacillus paracasei （LZ9089, LZ9Y10）, 1 strains of Lactobacillus casei （LZ9183） and 1 strains of Lactobacillus brevis （LZ9285）. Conclusion: Four strains with high exopolysaccharide yield have good basic probiotic characteristics and have potential development and utilization value.

The self-rectifying memristor (SRM) is a promising device prototype for high-density three-dimensional (3D) integration and high-efficiency in-memory computing (IMC) by virtue of its ability to effectively suppress sneak current, simple device structure, and low energy consumption. Theoretically understanding the intrinsic mechanisms of SRM is a matter of concern. Here, we fabricated a Ta/TaOx/HfO2/Pt-stacked SRM exhibiting >103 on/off ratio, rectification ratio, and nonlinearity. The SRM can be repeatedly programmed by more than 106 pulses and demonstrates robust retention and high scalability (∼59 Mbit). A reasonable interface model for this SRM is established based on first-principles calculations. Using self-energy corrected density function theory, we calculate the barrier heights at each interface. Detailed I–V curve fitting and energy band analysis are performed and computationally verified to explain the intrinsic reasons for resistive switching, self-rectifying, and nonlinear behaviors. The work may advance the development of SRM prototype to enable energy-efficient 3D IMC. [ABSTRACT FROM AUTHOR]

While ferroelectric hafnia (HfO2) has become a technically important material for microelectronics, the physical origin of its ferroelectricity remains poorly understood. The tetragonal P 4 2 / nmc phase is commonly assigned as its paraelectric mother phase but has no soft mode at the Brillouin zone center. In this work, we propose that the paraelectric—ferroelectric transition in the fluorite-type Pca21 ferroelectric family can be described by a Pcca — Pca 2 1 transition, where the Pcca mother phase will evolve into either the Pca 2 1 ferroelectric phase or the centrosymmetric P 2 1 / c monoclinic phase, depending on the strain conditions. The Pcca phase is directly linked to both phases in the context of continuous phase transition. Hafnia is regarded as a special case of this family in that it has accidental atomic degeneracy because all anions are oxygen. The theory is also correlated with the seven-coordination theory that explains the ferroelectricity in hafnia from a chemical perspective. In addition, the strain conditions to promote the ferroelectric phase in hafnia are discussed. [ABSTRACT FROM AUTHOR]

HfO2-based dielectrics are promising for nanoscale ferroelectric applications, and the most favorable material within the family is Zr-substituted hafnia, i.e., Hf1−xZrxO2 (HZO). The extent of Zr substitution can be great, and x is commonly set to 0.5. However, the bandgap of ZrO2 is lower than HfO2, thus it is uncertain how the Zr content should influence the electronic band structure of HZO. A reduced bandgap is detrimental to the cycling endurance as charge injection and dielectric breakdown would become easier. Another issue is regarding the comparison on the bandgaps between HfO2/ZrO2 superlattices and HZO solid-state solutions. In this work, we systematically investigated the electronic structures of HfO2, ZrO2, and HZO using self-energy corrected density functional theory. In particular, the conduction band minimum of Pca21-HfO2 is found to lie at an ordinary k-point on the Brillouin zone border, not related to any interlines between high-symmetry k-points. Moreover, the rule of HZO bandgap variation with respect to x has been extracted. The physical mechanisms for the exponential reduction regime and linear decay regime have been revealed. The bandgaps of HfO2/ZrO2 ferroelectric superlattices are investigated in a systematic manner, and the reason why the superlattice could possess a bandgap lower than that of ZrO2 is revealed through comprehensive analysis. [ABSTRACT FROM AUTHOR]

Background: Evidence suggests that type 2 diabetes (T2D) is an independent risk factor for Alzheimer's disease (AD), sharing similar pathophysiological traits like impaired insulin signaling. Objective: To test the association between plasma insulin and cerebrospinal fluid (CSF) AD pathology. Methods: A total of 304 participants were included in the Alzheimer's Disease Neuroimaging Initiative, assessing plasma insulin and CSF AD pathology. We explored the cross-sectional and longitudinal associations between plasma insulin and AD pathology and compared their associations across different AD clinical and pathological stages. Results: In the non-demented group, amyloid-β (Aβ)+ participants (e.g., as reflected by CSF Aβ42) exhibited significantly lower plasma insulin levels compared to non-demented Aβ–participants (p < 0.001). This reduction in plasma insulin was more evident in the A+T+ group (as shown by CSF Aβ42 and pTau181 levels) when compared to the A–T– group within the non-dementia group (p = 0.002). Additionally, higher plasma insulin levels were consistently associated with more normal CSF Aβ42 levels (p < 0.001) across all participants. This association was particularly significant in the Aβ–group (p = 0.002) and among non-demented individuals (p < 0.001). Notably, baseline plasma insulin was significantly correlated with longitudinal changes in CSF Aβ42 (p = 0.006), whereas baseline CSF Aβ42 did not show a similar correlation with changes in plasma insulin over time. Conclusions: These findings suggest an association between plasma insulin and early Aβ pathology in the early stages of AD, indicating that plasma insulin may be a potential predictor of changes in early Aβ pathology. [ABSTRACT FROM AUTHOR]

An unparalleled copper(I)-catalyzed synthesis of 1,3,4-oxadiazoles from tertiary amines in one step has been described. The one-pot reactions involving (N-isocyanimine)triphenylphosphorane, tertiary amines, and carboxylic acids resulted in the formation of 1,3,4-oxadiazoles in moderate to good yields through a consecutive oxidative Ugi/aza-Wittig reaction, enabling the direct functionalization of sp3 C-H bonds adjacent to the nitrogen atom. This method offered several notable advantages, including ligands-free, exceptional productivity and a high functional group tolerance. The preliminary biological evaluation demonstrated that compound 4f inhibited hepatoma cells efficiently, suggesting potentially broad applications of the approach for synthesis and medicinal chemistry. [ABSTRACT FROM AUTHOR]

Statistical tests for biomarker identification and classification methods for patient grouping are two important topics in adaptive designs of clinical trials related to genomic studies. In this article, we evaluate four test methods for biomarker identification in the first stage of an adaptive design: a model-based identification method, the popular two-sided t-test, the nonparametric Wilcoxon Rank-Sum test (two-sided), and the Regularized Generalized Linear Models. For patients grouping in the second stage, we examine classification methods such as Random Forest, Elastic-net Regularized Generalized Linear Models, Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and Extreme Gradient Boosting (XGBoost). Simulation studies are carried out to assess the performance of the different methods. The best identification methods are chosen based on the well-known F 1 score, while the best classification techniques are selected based on the area under a receiver operating characteristic curve (AUC). The chosen methods are then applied to the Adaptive Signature Design (ASD) with a real data set from breast cancer patients for the purpose of evaluating the performance of ASD in different situations. [ABSTRACT FROM AUTHOR]

Spinal microglia play a key role for creating exaggerated pain following tissues inflammation or injury. Electroacupuncture (EA) can effectively control the exaggerated pain both in humans with inflammatory disease and animals with experimental inflammatory pain. However, little is known about the relationship between spinal glial activation and EA analgesia. Using immunohistochemistry, RT-PCR analysis, and behavioral testing, the present study demonstrated that (1) Unilateral intra-articular injection of CFA produced a robust microglial activation and the up-regulation of the tumor necrosis factor (TNF)-α, interleukin (IL-1β), and IL-6 mRNA levels in the spinal cord; (2) Repeated intrathecal (i.t.) injection of minocycline (100 μg), a microglial inhibitor, or EA stimulation of ipsilateral “Huantiao”(GB30) and “Yanglingquan” (GB34) acupoints significantly suppressed CFA-induced nociceptive behavioral hypersensitivity and spinal microglial activation; (3) Combination of EA with minocycline significantly enhanced the inhibitory effects of EA on allodynia and hyperalgesia. For the first time, these data provide direct evidence for the involvement of spinal microglial functional state in anti-nociception of EA. Thus, anti-neuroinflammatory effect of EA might be considered as one of the mechanisms of its anti-arthritic pain effects, and thereby a multidisciplinary integrated approach to treating symptoms related to arthritis might be raised.

The wake‐up phenomenon widely exists in hafnia‐based ferroelectric capacitors, which causes device parameter variation over time. Crystallization at a higher temperature has been reported to be effective in eliminating wake‐up, but high temperature may yield the monoclinic phase or generate more oxygen vacancies. In this work, a unidirectional annealing method is proposed for the crystallization of Hf0.5Zr0.5O2 (HZO) superlattice ferroelectrics, which involves heating from the Pt/ZrO2 interface side. It is demonstrated that 600 °C annealing only leads to a moderate content of monoclinic phase in HZO, and the TiN/HZO/Pt capacitor exhibits wake‐up free nature and a switchable remnant polarization value of 27.4 µC cm−2. On the other hand, heating from the TiN/HfO2 side, or using 500 °C annealing temperature, could yield ferroelectric devices that require a wake‐up process. The special configuration of Pt/ZrO2 is verified by comparative studies with several other superlattice structures and HZO solid‐state solutions. It is discovered that heating from the Pt/HfO2 side at 600 °C leads to high leakage current and a memristor behavior. The mechanisms of ferroelectric phase stabilization and memristor formation have been discussed. The unidirectional heating method can also be useful for other hafnia‐based ferroelectric devices. [ABSTRACT FROM AUTHOR]

Establishing a systematic molecular information analysis strategy for cell culture models is of great significance for drug development and tissue engineering technologies. Here, we fabricated single silver nanowires with high surface-enhanced Raman scattering activity to extract SERS spectra in situ from two-dimensional (2D) and three-dimensional (3D) cell culture models. The silver nanowires were super long, flexible and thin enough to penetrate through multiple cells. A single silver nanowire was used in combination with a four-dimensional microcontroller as a cell endoscope for spectrally analyzing the components in cell culture models. Then, we adopted a machine learning algorithm to analyze the obtained spectra. Our results show that the abundance of proteins differs significantly between the 2D and 3D models, and that nucleic acid-rich and protein-rich regions can be distinguished with satisfactory accuracy. [ABSTRACT FROM AUTHOR]