Governor Celebrates Funding for Mattapan Community Health Center

BACKGROUND:There is no single standard chemotherapy regimen for elderly patients with advanced gastric cancer (AGC). A phase III trial has confirmed that both capecitabine monotherapy and capecitabine plus oxaliplatin are well tolerated for elderly patients with AGC, but their economic influence in China is unknown. OBJECTIVE:The purpose of this cost-effectiveness analysis was to estimate the effects of capecitabine monotherapy and capecitabine plus oxaliplatin in elderly patients with AGC on health and economic outcomes in China. METHODS:We created a Markov model based on data from a Korean clinical phase III trial to analyze the cost-effectiveness of the treatment of elderly patients in the capecitabine monotherapy (X) group and capecitabine plus oxaliplatin (XELOX) group. The costs were obtained from published reports and the local health system. The utilities were assumed on the basis of the published literature. Costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICER) were estimated. One-way and probabilistic sensitivity analyses (Monte Carlo simulations) were performed. RESULTS:In the cost-effectiveness analysis, X had a lower total cost ($45,731.68) and cost-effectiveness ratio ($65,918.93/QALY). The one-way sensitivity analysis suggested that the most influential parameter was the risk of requiring second-line chemotherapy in XELOX group. The probabilistic sensitivity analysis predicted that the X regimen was cost-effective 100% of the time, given a willingness-to-pay threshold of $26,598. CONCLUSIONS:Our findings show that the XELOX regimen is less cost-effective compared to the X regimen for elderly patients with AGC in China from a Chinese healthcare perspective

Fully Conjugated Phthalocyanine Copper Metal-Organic Frameworks for Sodium-Iodine Batteries with Long-Time-Cycling Durability

Rechargeable sodium-iodine (Na-I-2) batteries are attracting growing attention for grid-scale energy storage due to their abundant resources, low cost, environmental friendliness, high theoretical capacity (211 mAh g(-1)), and excellent electrochemical reversibility. Nevertheless, the practical application of Na-I-2 batteries is severely hindered by their poor cycle stability owing to the serious dissolution of polyiodide in the electrolyte during charge/discharge processes. Herein, the atomic modulation of metal-bis(dihydroxy) species in a fully conjugated phthalocyanine copper metal-organic framework (MOF) for suppression of polyiodide dissolution toward long-time cycling Na-I-2 batteries is demonstrated. The Fe-2[(2,3,9,10,16,17,23,24-octahydroxy phthalocyaninato)Cu] MOF composited with I-2 (Fe-2-O-8-PcCu/I-2) serves as a cathode for a Na-I-2 battery exhibiting a stable specific capacity of 150 mAh g(-1) after 3200 cycles and outperforming the state-of-the-art cathodes for Na-I-2 batteries. Operando spectroelectrochemical and electrochemical kinetics analyses together with density functional theory calculations reveal that the square planar iron-bis(dihydroxy) (Fe-O-4) species in Fe-2-O-8-PcCu are responsible for the binding of polyiodide to restrain its dissolution into electrolyte. Besides the monovalent Na-I-2 batteries in organic electrolytes, the Fe-2-O-8-PcCu/I-2 cathode also operates stably in other metal-I-2 batteries like aqueous multivalent Zn-I-2 batteries. Thus, this work offers a new strategy for designing stable cathode materials toward high-performance metal-iodine batteries

Real-time scheduling of renewable power systems through planning-based reinforcement learning

The growing renewable energy sources have posed significant challenges to traditional power scheduling. It is difficult for operators to obtain accurate day-ahead forecasts of renewable generation, thereby requiring the future scheduling system to make real-time scheduling decisions aligning with ultra-short-term forecasts. Restricted by the computation speed, traditional optimization-based methods can not solve this problem. Recent developments in reinforcement learning (RL) have demonstrated the potential to solve this challenge. However, the existing RL methods are inadequate in terms of constraint complexity, algorithm performance, and environment fidelity. We are the first to propose a systematic solution based on the state-of-the-art reinforcement learning algorithm and the real power grid environment. The proposed approach enables planning and finer time resolution adjustments of power generators, including unit commitment and economic dispatch, thus increasing the grid's ability to admit more renewable energy. The well-trained scheduling agent significantly reduces renewable curtailment and load shedding, which are issues arising from traditional scheduling's reliance on inaccurate day-ahead forecasts. High-frequency control decisions exploit the existing units' flexibility, reducing the power grid's dependence on hardware transformations and saving investment and operating costs, as demonstrated in experimental results. This research exhibits the potential of reinforcement learning in promoting low-carbon and intelligent power systems and represents a solid step toward sustainable electricity generation.Comment: 12 pages, 7 figure

First-line treatments for extensive-stage small-cell lung cancer with immune checkpoint inhibitors plus chemotherapy: a China-based cost-effectiveness analysis

ObjectiveTo determine the cost-effectiveness of imported immune checkpoint inhibitors (ICIs) such as atezolizumab and durvalumab, and domestic ICIs like serplulimab and adebrelimab, in combination with chemotherapy for extensive-stage small cell lung cancer (ES-SCLC) in China.MethodsUsing a 21-day cycle length and a 20-year time horizon, a Markov model was established to compare the clinical and economic outcomes of five first-line ICIs plus chemotherapy versus chemotherapy alone, as well as against each other, from the perspective of the Chinese healthcare system. Transition probabilities were estimated by combining the results of the CAPSTONE-1 trial and a published network meta-analysis. Cost and health state utilities were collected from multiple sources. Both cost and effectiveness outcomes were discounted at a rate of 5% annually. The primary model output was incremental cost-effectiveness ratios (ICERs). A series of sensitivity analyses were preformed to assess the robustness of the model.ResultsIn the base-case analysis, the addition of first-line ICIs to chemotherapy resulted in the ICERs ranged from $80,425.31/QALY to$812,415.46/QALY, which exceeded the willing-to-pay threshold set for the model. When comparing these first-line immunochemotherapy strategies, serplulimab plus chemotherapy had the highest QALYs of 1.51286 and the second lowest costs of $60,519.52, making it is the most cost-effective strategy. Our subgroup-level analysis yielded results that are consistent with the base-case analysis. The sensitivity analysis results confirmed the validity and reliability of the model.ConclusionIn China, the combination of fist-line ICIs plus chemotherapy were not considered cost-effective when compared to chemotherapy alone. However, when these fist-line immunochemotherapy strategies were compared with each other, first-line serplulimab plus chemotherapy consistently demonstrated superiority in terms of cost-effectiveness. Reducing the cost of serplulimab per 4.5 mg/kg would be a realistic step towards making first-line serplulimab plus chemotherapy more accessible and cost-effective