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Objectives: To assess the efficacy and tolerability of iGlarLixi—a novel, fixed-ratio, soluble combination of insulin glargine and lixisenatide—for the treatment of type 2 diabetes (T2D). Methods: The PubMed, Embase, Cochrane Library and ClinicalTrials.gov databases were searched from inception to November 15, 2023 to identify randomized controlled trials (RCTs) comparing iGlarLixi with a placebo or any other antidiabetic agent in adults with T2D. Risk ratios (RRs) and mean differences (MDs) with 95% confidence intervals (CIs) were calculated to evaluate the outcomes. Results: A total of 10 trials enrolling 6071 T2D patients were included. Compared with placebos or other antidiabetic agents, iGlarLixi exerted beneficial effects on changes in HbA1c, the percentage of patients who achieved an HbA1c < 7%, the percentage of patients who achieved an HbA1c < 6.5%, the percentage of patients who achieved an HbA1c < 7.0% without weight gain and/or without severe or blood glucose-confirmed hypoglycemic episodes, changes in fasting plasma glucose, and changes in self-measured plasma glucose. Regarding safety, iGlarLixi did not increase the incidence of severe hypoglycemia or serious adverse events but did increase the incidence of gastrointestinal adverse events, symptomatic hypoglycemia, and adverse events (e.g., nausea, vomiting, diarrhea). Conclusions: iGlarLixi showed improved efficacy and safety in patients with T2D. Additional large, multicenter RCTs are warranted to obtain deeper insights into the efficacy and safety of iGlarLixi, thereby providing guidance for clinical treatment decisions.

The effect of targeted therapy for metastatic hepatocellular carcinoma (HCC) is still unsatisfactory. Exploring the underlying mechanism of HCC metastasis is favorable to provide new therapeutic strategies. T-box (TBX) transcription factor family genes, which are crucial regulators in embryo and organ development, are vital for regulating tumor initiation, growth and metastasis. Here we explored the role of TBX19 in HCC metastasis, which is one of the most upregulated TBX family genes in human HCC tissues. TBX19 expression was markedly upregulated in HCC tissues and elevated TBX19 expression predicted poor prognosis. Overexpression of TBX19 enhanced HCC metastasis through upregulating epidermal growth factor receptor (EGFR) and Rac family small GTPase 1 (RAC1) expression. Downregulation of EGFR and RAC1 inhibited TBX19-mediated HCC metastasis, while upregulation of EGFR and RAC1 restored inhibition of HCC metastasis mediated by TBX19 knockdown. Furthermore, epidermal growth factor (EGF)/EGFR signaling upregulated TBX19 expression via the extracellular signal-regulated kinase (ERK)/nuclear factor (NF)-kB axis. Besides, the combined application of EGFR inhibitor Erlotinib and RAC1 inhibitor NSC23766 markedly inhibited TBX19-mediated HCC metastasis. In HCC cohorts, TBX19 expression was positively associated with EGFR and RAC1 expression. Patients with positive coexpression of TBX19/EGFR or TBX19/RAC1 displayed the poorest prognosis. In conclusion, EGF/EGFR signaling upregulated TBX19 expression via ERK/NF-kB pathway and TBX19 fostered HCC metastasis by enhancing EGFR and RAC1 expression, which formed an EGF-TBX19-EGFR positive feedback loop. Targeting this signaling pathway may offer a potential therapeutic strategy to efficiently restrain TBX19-mediated HCC metastasis.

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The critical bottleneck of electrocatalytic CO2reduction reaction (CO2RR) lies in its low efficiency at high overpotential caused by competitive hydrogen evolution. It is challenging to develop an efficient catalyst achieving both high current density and high Faradaic efficiency (FE) for CO2RR. Herein, we synthesized fluorine-doped cagelike porous carbon (F-CPC) by purposely tailoring its structural properties. The optimized F-CPC possesses large surface area with moderate mesopore and abundant micropores as well as high electrical conductivity. When used as catalyst for CO2RR, F-CPC exhibits FE of 88.3% for CO at −1.0 V vsRHE with a current density of 37.5 mA·cm –2. Experimental results and finite element simulations demonstrate that the excellent CO2RR performance of F-CPC at high overpotential should be attributed to its structure-enhanced electrocatalytic process stemming from its cagelike morphology.

The structure of an electrode material has an important impact on the performance of a capacitive deionization (CDI) device. However, it is still a challenge to design and synthesize electrode materials with a rational structure based on deep understanding of their structure-dependent CDI performance. Herein, we report the preparation of carbon nanocages (CNCs) with regulated shell thickness and a rich pore structure as an advanced material for high-performance CDI electrodes. The as-prepared CNC has a considerable specific capacitance of 149 F g–1at a scan rate of 5 mV s–1. When used as CDI electrodes, the CNC shows an outstanding electrosorption ability of 17.5 mg g–1at 1.4 V at an initial concentration of 250 mg L–1NaCl solution. Furthermore, the CNC electrode displays high salt adsorption rate and good cyclic stability. Finite element simulations reveal that the superior structure of the CNC substantially promotes the ion transfer rate by shortening ion diffusion paths in the cavity of the electrode material. Also, both inner and outer walls of the CNC provide sufficient active sites for fast adsorption and desorption of salty ions. This work not only demonstrates that the CNC is a potential electrode material for CDI applications but also paves a way to design and prepare high-performance electrode materials based on a new perspective on their structure–performance relationship.

Charge batch planning is the bottleneck of production management planning in iron and steelmaking enterprises. The optimization of the charge batch planning process will directly influence the iron and steelmaking cost, production and energy consumption. In this paper, an effective mathematical model based on multi-objective weighting method is built up to describe the multi-performance indexes and the multi-constraints; an efficiency adaptive search algorithm based on linear augmented Lagrangian relaxation framework is proposed to alleviate the problem of sawtooth oscillation when the traditional Lagrangian algorithm searches within the feasible domain. The strategy proposed in this paper is verified based on the background of the actual steelmaking and continuous casting management process in China steelmaking plant. The optimization results guarantee the solution quality and speed of charge batch planning of steelmaking-continuous casting.

The catalysts performance degradation is a crucial issue in decay of the polymer electrolyte membrane fuel cell (PEMFC). The effect of Nafion content, dispersity of Pt nanoparticles and selected types of carbon support on the degradation of electrochemical surface area (ECSA) and double layer capacitance (DLC) were experimentally discussed by accelerated stress test (AST). The catalyst with 20wt% Nafion content exhibited better catalyst performance. i.e., the less DLC and ECSA degradation during AST. Catalysts with well Pt dispersity showed superior %ECSA (the percentage change of ECSA) retention. The heat-treated catalysts exhibited the lowest ECSA and DLC degradation rate due to the larger Pt particle and high carbon corrosion resistance. Moreover, a multi-order model describing the correlation between ECSA and DLC degradation was proposed, providing a vital reference for quantitatively investigating ECSA and DLC degradation in the catalysts with different catalysts structural parameters.

The steelmaking-continuous casting batch planning plays an important role in the relationship between the Enterprise Resource Planning (ERP) layer and the Manufacturing Execution System (MES) layer. The charge batch planning is one of the important links in the steelmaking-continuous casting batch planning. Efficient optimization of charge batch planning can reduce energy consumption and improve the profit of the enterprise. As the production scale of iron and steel enterprises increases, the number of orders increases exponentially, and the optimization goal becomes more and more complicated, which makes it difficult to ensure the optimization efficiency while ensuring the quality of optimization results. Aiming at this problem, this paper proposes a multi-performance index mixed integer programming model considering actual production, and solves it based on the order decomposition strategy under the linearized Augmented Lagrangian framework. Finally, experiments show that the proposed algorithm can effectively improve the compilation efficiency and quality of the charge batch planning compared with the traditional Lagrangian Relaxation algorithm.

Gene regulation is a complex non-equilibrium process. Here, we show that quantitating the temporal regulation of key gene states (transcriptionally inactive, active, and refractory) provides a parsimonious framework for analyzing gene regulation. Our theory makes two non-intuitive predictions. First, for transcription factors (TFs) that regulate transcription burst frequency, as opposed to amplitude or duration, weak TF binding is sufficient to elicit strong transcriptional responses. Second, refractoriness of a gene after a transcription burst enables rapid responses to stimuli. We validate both predictions experimentally by exploiting the natural, optogenetic-like responsiveness of the NeurosporaGATA-type TF White Collar Complex (WCC) to blue light. Further, we demonstrate that differential regulation of WCC target genes is caused by different gene activation rates, not different TF occupancy, and that these rates are tuned by both the core promoter and the distance between TF-binding site and core promoter. In total, our work demonstrates the relevance of a kinetic, non-equilibrium framework for understanding transcriptional regulation.