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Novel hydrogen sulfide donor-based fibrate derivatives were synthesized and assessed for hypolipidemic and hepatoprotective effects in Triton WR-1339-induced hyperlipidemic mice. After preliminary screening of the target compounds, T5 exhibited significant hypolipidemic effects, reducing triglycerides (TG) and total cholesterol (TC). The action of T5 in reducing TG and TC levels is dose-dependent. Through molecular docking and protein expression analysis, it was found that T5 may exert hypolipidemic effects by activating the PPAR-α receptor. Examination of liver tissue from hyperlipidemic mice supplemented with T5 demonstrated a marked decrease in hepatic lipid buildup. Furthermore, there was a significant amelioration in the levels of hepatic transaminases (AST and ALT) that were elevated as a result of hyperlipidemia. As designed, T5 exhibited H2S-releasing effects in a hyperlipidemia model. Additionally, T5 has the capability to ameliorate the lipid peroxidation process triggered by hyperlipidemia, leading to a reduction in malondialdehyde (MDA) levels. These findings further support the potential of T5 as a hypolipidemic agent with hepatoprotective properties.

Abstract Background This study aims to compare the clinical outcomes and safety of a novel hand-held retractor system-assisted Wiltse TLIF with that P-TLIF and assess whether this hand-held retractor system assisted Wiltse TLIF can yield less paraspinal muscle injury. Methods 56 patients (P-TLIF: 26, Wiltse TLIF: 30) were included in this one year prospective controlled study. The operation time, intraoperative blood loss, postoperative drainage, mobilization time, and discharge time were recorded. The clinical outcomes were evaluated by ODI, VAS, JOA, and SF-36 scores (7 days, 3, 6, and 12 months after surgery). Paraspinal muscle injury was assessed by postoperative MRI (6 months after surgery). CK and C-reaction protein were measured pre and postoperatively, and CT or X-ray (one year postoperatively) was used to assess bony union/non-union. Results The Wiltse (study) group was associated with significantly less estimated blood loss (79.67 ± 28.59 ml vs 192.31 ± 59.48 ml, P = 0.000*), postoperative drainage (43.33 ± 27.89 ml vs 285.57 ± 123.05 ml, P = 0.000*), and shorter mobilization (4.1 ± 1.2 d vs. 3.0 ± 0.9 d, P

Abstract Background The essential roles of platelets in thrombosis have been well recognized. Unexpectedly, thrombosis is prevalent during thrombocytopenia induced by cytotoxicity of biological, physical and chemical origins, which could be suffered by military personnel and civilians during chemical, biological, radioactive, and nuclear events. Especially, thrombosis is considered a major cause of mortality from radiation injury-induced thrombocytopenia, while the underlying pathogenic mechanism remains elusive. Methods A mouse model of radiation injury-induced thrombocytopenia was built by exposing mice to a sublethal dose of ionizing radiation (IR). The phenotypic and functional changes of platelets and megakaryocytes (MKs) were determined by a comprehensive set of in vitro and in vivo assays, including flow cytometry, flow chamber, histopathology, Western blotting, and chromatin immunoprecipitation, in combination with transcriptomic analysis. The molecular mechanism was investigated both in vitro and in vivo, and was consolidated using MK-specific knockout mice. The translational potential was evaluated using a human MK cell line and several pharmacological inhibitors. Results In contrast to primitive MKs, mature MKs (mMKs) are intrinsically programmed to be apoptosis-resistant through reprogramming the Bcl-xL-BAX/BAK axis. Interestingly, mMKs undergo minority mitochondrial outer membrane permeabilization (MOMP) post IR, resulting in the activation of the cyclic GMP-AMP synthase-stimulator of IFN genes (cGAS-STING) pathway via the release of mitochondrial DNA. The subsequent interferon-β (IFN-β) response in mMKs upregulates a GTPase guanylate-binding protein 2 (GBP2) to produce large and hyperreactive platelets that favor thrombosis. Further, we unmask that autophagy restrains minority MOMP in mMKs post IR. Conclusions Our study identifies that megakaryocytic mitochondria-cGAS/STING-IFN-β-GBP2 axis serves as a fundamental checkpoint that instructs the size and function of platelets upon radiation injury and can be harnessed to treat platelet pathologies.

Thin-film transistors play an important role in ultra-high definition displays. The conventional physical model requires a significant amount of time and resources, while its generalizability is limited. This paper introduces a method for quickly incorporating the characteristics of emerging devices into circuit simulations using an artificial neural network (ANN) model. The multi-layer perceptron (MLP) model, with a simple structure and high modeling efficiency, is employed as a typical ANN model. The pivotal step in using the MLP model is to determine its topology. This hyperparameter problem can be easily solved using Bayesian search. To improve the accuracy of the model, a genetic algorithm is proposed to optimize the initial values of the weights and biases. Furthermore, by introducing the first derivative in the loss function, small signal parameters can be taken into consideration. This modeling approach significantly reduces the time required for compact device modeling. Our experimental results exhibit a strong correlation between the model’s output and the corresponding experimental data, thereby providing comprehensive validation for the effectiveness of our proposed model. Once the trained model parameters were extracted, we implemented the hybrid ANN model using Verilog-A. This circuit-level experiment demonstrates that this hybrid ANN model can accurately estimate various physical devices and circuits.

The ergot alkaloids are a class of natural products known for their pharmacologically privileged molecular structure that are used in the treatment of neurological ailments. Here the authors report on the production of the ergot (fungus)-derived therapeutic precursor, D-lysergic acid (DLA), in baker’s yeast.

Abstract Aims/Introduction To investigate the efficacy/safety of dulaglutide once‐weekly monotherapy versus glimepiride in Chinese patients with type 2 diabetes. Materials and Methods This was a post‐hoc analysis of a Chinese randomized, double‐blind, non‐inferiority, phase III study. Patients (n = 572) with inadequate glycemic control received dulaglutide 1.5 mg (n = 189) or 0.75 mg (n = 194) once‐weekly or glimepiride (1–3 mg/day; n = 189) for 26 weeks. The primary objective of the study was to investigate the non‐inferiority of dulaglutide 1.5 mg versus glimepiride by the change from baseline to week 26 in glycated hemoglobin (non‐inferiority margin 0.4%). Results Dulaglutide 1.5 mg and 0.75 mg were non‐inferior (P

Abstract Flexible pressure sensors (FPS) have shown wide applications in artificial robotics, wearable devices, electronic skins, and biomedical systems; however, complicated procedures like micromachining and micromolding are often involved to achieve high performance of the sensor. In this work, a novel capacitive FPS was prepared by using silver nanowire (AgNW)-paper substrates as electrodes and polydimethylsiloxane (PDMS) as dielectrics, and results revealed that the sensitivity and dynamic range of the as-prepared sensor were 1.05 kPa−1 and 1 Pa to 2 kPa, respectively, which were comparable to the state-of-the-art ones; practical application measurements further indicated that the capacitive FPS was capable of detecting bending, finger tap, and human speech as well as identifying object profile; therefore, it shows good potential for applying in artificial skin and wearable devices.

Social influence is the key factor to drive information propagation in online social networks and can be modeled and analyzed with social networking data.As a kind of classical personal influence algorithm,two parallel implementation versions of a PageRank based method were introduced.Furthermore,extensive experiments were conducted on a large-scale real dataset to test the performance of these parallel methods in a distributed environment.The results demonstrate that the computational efficiency of the personal influence algorithm can be improved significantly in massive data sets by virtue of existing big data processing framework,and provide an empirical reference for the future research and optimization of the algorithm as well.

Enzyme engineering is an indispensable tool in the field of synthetic biology, where enzymes are challenged to carry out novel or improved functions. Achieving these goals sometimes goes beyond modifying the primary sequence of the enzyme itself. The use of protein or nucleic acid scaffolds to enhance enzyme properties has been reported for applications such as microbial production of chemicals, biosensor development and bioremediation. Key advantages of using these assemblies include optimizing reaction conditions, improving metabolic flux and increasing enzyme stability. This review summarizes recent trends in utilizing genetically encodable scaffolds, developed in line with synthetic biology methodologies, to complement the purposeful deployment of enzymes. Current molecular tools for constructing these synthetic enzyme-scaffold systems are also highlighted.

The recent development of the mobile Internet and the rise of social media have significantly enriched the way people access information. Accurate modeling of the probability of information propagation between users is essential for studying information dissemination issues in social networks. As the dissemination of information is inseparable from the interactions between users, the probability of propagation can be characterized by such interactions. In general, there are differences in the dissemination modes of information that carry different topics in a real social network. Using these factors, we propose a method (TMIVM) to measure the mutual influence between users at the topic level. The method associates two vectorization parameters for each user—an influence vector and a susceptibility vector—where the dimensions of the vector represent different topic categories. The magnitude of the mutual influence between users on different topics can be obtained by the product of the corresponding elements of the vectors. Specifically, in this article, we fit a social network historical information cascade data through Survival Analysis to learn the parameters of the influence and susceptibility vectors. The experimental results on a synthetic data set and a real Microblog data set show that this method better measures the propagation probability and information cascade predictions compared to other methods.

The expression levels of genes involved in drug and nutrient absorption were evaluated in the Madin-Darby Canine Kidney (MDCK) in vitro drug absorption model. MDCK cells were grown on plastic surfaces (for 3 days) or on Transwell® membranes (for 3, 5, 7, and 9 days). The expression profile of genes including ABC transporters, SLC transporters, and cytochrome P450 (CYP) enzymes was determined using the Affymetrix® Canine GeneChip®. Expression of genes whose probe sets passed a stringent confirmation process was examined. Expression of a few transporter (MDR1, PEPT1 and PEPT2) genes in MDCK cells was confirmed by RT-PCR. The overall gene expression profile was strongly influenced by the type of support the cells were grown on. After 3 days of growth, expression of 28% of the genes was statistically different (1.5-fold cutoff, p < 0.05) between the cells grown on plastic and Transwell® membranes. When cells were differentiated on Transwell® membranes, large changes in gene expression profile were observed during the early stages, which then stabilized after 5–7 days. Only a small number of genes encoding drug absorption related SLC, ABC, and CYP were detected in MDCK cells, and most of them exhibited low hybridization signals. Results from this study provide valuable reference information on endogenous gene expression in MDCK cells that could assist in design of drug-transporter and/or drug-enzyme interaction studies, and help interpret the contributions of various transporters and metabolic enzymes in studies with MDCK cells.

Online learning platforms have become important learning tools, and online learning replaced face-to-face teaching as the primary learning method of students during COVID-19. However, there have been few systematic studies on learning effectiveness and its influential factors. This study was based on fuzzy-set qualitative comparative analysis (fsQCA) to explore the joint effects of multiple factors on online learning effectiveness for tourism and hospitality students from the dual perspective of the platform and individual. The results revealed five antecedent combinations that led to high-quality online learning, which were categorized into "platform-individual" internal and external promotion paths and "function-interaction" platform environment promotion paths. Moreover, there were substitution effects in the paths to high-quality online learning; specifically, perceived usefulness (PU) and perceived ease of use (PEU) were substitutable, and perceived playfulness (PP), learning attitude (LA), and self-efficacy (SE) could replace each other. Finally, self-efficacy was not a necessary condition for efficient online learning. Our findings highlight substitution relationships among the influencing factors of online learning effectiveness from a configuration perspective and further reveal the internal micromechanisms of achieving high-quality online learning.