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Carbon mitigation technologies lead to air quality improvement and health co-benefits, while the practical effects of the technologies are dependent on the energy composition, technological advancements, and economic development. In China, mitigation technologies such as end-of-pipe treatment, renewable energy adoption, carbon capture and storage (CCS), and sector electrification demonstrate significant promise in meeting carbon reduction targets. However, the optimization of these technologies for maximum co-benefits remains unclear. Here, we employ an integrated assessment model (AIM/enduse, CAM-chem, IMED|HEL) to analyze air quality shifts and their corresponding health and economic impacts at the provincial level in China within the two-degree target. Our findings reveal that a combination of end-of-pipe technology, renewable energy utilization, and electrification yields the most promising results in air quality improvement, with a reduction of fine particulate matter (PM2.5) by -34.6 µg m-3 and ozone by -18.3 ppb in 2050 compared to the reference scenario. In contrast, CCS technology demonstrates comparatively modest improvements in air quality (-9.4 µg m-3 for PM2.5 and -2.4 ppb for ozone) and cumulative premature deaths reduction (-3.4 million from 2010 to 2050) compared to the end-of-pipe scenario. Notably, densely populated regions such as Henan, Hebei, Shandong, and Sichuan experience the most health and economic benefits. This study aims to project effective future mitigation technologies and climate policies on air quality improvement and carbon mitigation. Furthermore, it seeks to delineate detailed provincial-level air pollution control strategies, offering valuable guidance for policymakers and stakeholders in pursuing sustainable and health-conscious environmental management.
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Economic productivity depends on reliable access to electricity, but the extreme shortage events of variable wind-solar systems may be strongly affected by climate change. Here, hourly reanalysis climatological data are leveraged to examine historical trends in defined extreme shortage events worldwide. We find uptrends in extreme shortage events regardless of their frequency, duration, and intensity since 1980. For instance, duration of extreme low-reliability events worldwide has increased by 4.1 hours (0.392 hours per year on average) between 1980-2000 and 2001-2022. However, such ascending trends are unevenly distributed worldwide, with a greater variability in low- and middle-latitude developing countries. This uptrend in extreme shortage events is driven by extremely low wind speed and solar radiation, particularly compound wind and solar drought, which however are strongly disproportionated. Only average 12.5% change in compound extremely low wind speed and solar radiation events may give rise to over 30% variability in extreme shortage events, despite a mere average 1.0% change in average wind speed and solar radiation. Our findings underline that wind-solar systems will probably suffer from weakened power security if such uptrends persist in a warmer future.
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Background and Objectives: The Alberta Stroke Program CT Score (ASPECTS) is a widely used rating system for assessing infarct extent and location. We aimed to investigate the prognostic value of ASPECTS subregions' involvement in the long-term functional outcomes of acute ischemic stroke (AIS). Materials and Methods: Consecutive patients with AIS and anterior circulation large-vessel stenosis and occlusion between January 2019 and December 2020 were included. The ASPECTS score and subregion involvement for each patient was assessed using posttreatment magnetic resonance diffusion-weighted imaging. Univariate and multivariable regression analyses were conducted to identify subregions related to 3-month poor functional outcome (modified Rankin Scale scores, 3-6) in the reperfusion and medical therapy cohorts, respectively. In addition, prognostic efficiency between the region-based ASPECTS and ASPECTS score methods were compared using receiver operating characteristic curves and DeLong's test. Results: A total of 365 patients (median age, 64 years; 70% men) were included, of whom 169 had poor outcomes. In the reperfusion therapy cohort, multivariable regression analyses revealed that the involvement of the left M4 cortical region in left-hemisphere stroke (adjusted odds ratio [aOR] 5.39, 95% confidence interval [CI] 1.53-19.02) and the involvement of the right M3 cortical region in right-hemisphere stroke (aOR 4.21, 95% CI 1.05-16.78) were independently associated with poor functional outcomes. In the medical therapy cohort, left-hemisphere stroke with left M5 cortical region (aOR 2.87, 95% CI 1.08-7.59) and caudate nucleus (aOR 3.14, 95% CI 1.00-9.85) involved and right-hemisphere stroke with right M3 cortical region (aOR 4.15, 95% CI 1.29-8.18) and internal capsule (aOR 3.94, 95% CI 1.22-12.78) affected were related to the increased risks of poststroke disability. In addition, region-based ASPECTS significantly improved the prognostic efficiency compared with the conventional ASPECTS score method. Conclusion: The involvement of specific ASPECTS subregions depending on the affected hemisphere was associated with worse functional outcomes 3 months after stroke, and the critical subregion distribution varied by clinical management. Therefore, region-based ASPECTS could provide additional value in guiding individual decision making and neurological recovery in patients with AIS.
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RATIONALE AND OBJECTIVES: Investigate the feasibility of using deep learning-based accelerated 3D T1-weighted volumetric isotropic turbo spin-echo acquisition (VISTA) for vessel wall magnetic resonance imaging (VW-MRI), compared to traditional Compressed SENSE and optimize acceleration factor (AF) to obtain high-quality clinical images. METHODS: 40 patients with atherosclerotic plaques in the intracranial or carotid artery were prospectively enrolled in our study from October 1, 2022 to October 31, 2023 underwent high-resolution vessel wall imaging on a 3.0 T MR system using variable Compressed SENSE (CS) AFs and reconstructed by an optimized artificial intelligence constrained Compressed SENSE (CS-AI). Images were reconstructed through both traditional CS and optimized CS-AI. Two radiologists qualitatively assessed the image quality scores of CS and CS-AI across different segments and quantitatively evaluated SNR (signal-to-noise ratio) and CNR (contrast-to-noise ratio) metrics. Paired t-tests, ANOVA, and Friedman tests analyzed image quality metrics. Written informed consent was obtained from all patients in this study. RESULTS: CS-AI groups demonstrated good image quality scores compared to reference scans until AF up to 12 (P < 0.05). The CS-AI 10 protocol provided the best images in the lumen of both normal and lesion sites (P < 0.05). The plaque SNR was significantly higher in CS-AI groups compared to CS groups until the AF increased to 12 (P < 0.05). CS-AI protocols had higher CNR compared to CS with whichever AF on both pre-and post-contrast T1WI (P < 0.05), The CNR was highest in the CS-AI 10 protocol on pre-contrast T1WI and in CS-AI 12 on post-contrast T1WI (P < 0.05). CONCLUSION: The study demonstrated the feasibility of using CS-AI technology to diagnose arteriosclerotic vascular disease with 3D T1 VISTA sequences. The image quality and diagnostic efficiency of CS-AI images were comparable or better than traditional CS images. Higher AFs are feasible and have potential for use in VW-MRI. The determination of standardized AFs for clinical scanning protocol is expected to help for empirical evaluation of new imaging technology.
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Background: In Chinese medicine, the mental focus and emotional stability of acupuncturists are key to optimal clinical outcomes. Many renowned acupuncturists utilize Traditional Chinese Qigong practices to enhance their concentration and emotional regulation abilities. Nevertheless, the existing literature lacks comprehensive evidence addressing this matter. Methods: This study will enroll 99 acupuncturists and randomly allocate them to one of three groups: Baduanjin, aerobic exercise, or a waiting-list control. The Baduanjin group will undertake 24 weeks of training, with three one-hour sessions weekly. The aerobic group will engage in brisk walking for the same duration and frequency. The control group will not receive any specific training. Assessments of emotion regulation, attention, cognitive functions, finger sensation, and athletic ability will be conducted at baseline (-1 week), mid-intervention (12 weeks), and post-intervention (24 weeks). Additionally, 20 participants from each group will undergo fMRI scans before and after the intervention to explore brain functional and structural changes relating to emotion, attention, cognition, motor skills, and sensory perception. Discussion: This study aims to contribute valuable insights into the effectiveness of Qigong practice, specifically Baduanjin, in enhancing emotional regulation, attention, and cognitive functions in acupuncturists and to investigate the neuroimaging mechanisms behind these effects. Ethics and dissemination: Approved by the Sichuan Regional Ethics Review Committee on Traditional Chinese Medicine (No. 2023KL - 118) and adhering to the Declaration of Helsinki. Results will be shared through policy briefs, workshops, peer-reviewed journals, and conferences.Clinical trial registrationwww.chictr.org.cn, ChiCTR2300076447.
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A transition away from coal power always maintains a high level of complexity as there are several overlapping considerations such as technical feasibility, economic costs, and environmental and health impacts. Here, we explore the cost-effectiveness uncertainty brought by policy implementation disturbances of different coal power phaseout and new-built strategies (i.e., the disruption of phaseout priority) in China based on a developed unit-level uncertainty assessment framework. We reveal the opportunity and risk of coal transition decisions by employing preference analysis. We find that, the uncertainty of a policy implementation might lead to potential delays in yielding the initial positive annual net benefits. For example, a delay of six years might occur when implementing the prior phaseout practice. A certain level of risk remains in the implementation of the phaseout policy, as not all strategies can guarantee the cumulative positive net benefits from 2018-2060. Since the unit-level heterogeneities shape diverse orientation of the phaseout, the decision-making preferences would remarkably alter the selection of a coal power transition strategy. More strikingly, the cost-effectiveness uncertainty might lead to missed opportunities in identifying an optimal strategy. Our results highlight the importance of minimizing the policy implementation disturbance, which helps mitigate the risk of negative benefits and strengthen the practicality of phaseout decisions.
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China's carbon-neutral target could have benefits for ambient fine particulate matter (PM2.5)-associated mortality. Although previous studies have researched such benefits, the potential impact on cardiovascular disease incidence burden is yet to be investigated thoroughly. Here, we first estimate the association between short-term PM2.5 exposure and the incidence of stroke and coronary heart disease (CHD) via a case-crossover study before projecting future changes in short-term PM2.5-associated excess incidence across China from 2025 to 2060 under three different emission scenarios. We find that, compared to the 2015-2020 baseline, average PM2.5 concentrations nationwide in 2060 under SSP119 (an approximation of a carbon-neutral scenario) are projected to decrease by 81.07%. The short-term PM2.5-related excess incidence of stroke and CHD is projected to be reduced to 3,352 cases (95% confidence interval: 939, 5,738)-compared with 34,485 cases under a medium-emissions scenario (SSP245)-and is expected to be accompanied by a 95% reduction in the related economic burden. China's carbon-neutral policies are likely to bring health benefits for cardiovascular disease by reducing short-term PM2.5-related incidence burden.
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BACKGROUND AND PURPOSE: Accelerating the image acquisition speed of MR imaging without compromising the image quality is challenging. This study aimed to evaluate the feasibility of contrast-enhanced (CE) 3D T1WI and CE 3D-FLAIR sequences reconstructed with compressed sensitivity encoding artificial intelligence (CS-AI) for detecting brain metastases (BM) and explore the optimal acceleration factor (AF) for clinical BM imaging. MATERIALS AND METHODS: Fifty-one patients with cancer with suspected BM were included. Fifty participants underwent different customized CE 3D-T1WI or CE 3D-FLAIR sequence scans. Compressed SENSE encoding acceleration 6 (CS6), a commercially available standard sequence, was used as the reference standard. Quantitative and qualitative methods were used to evaluate image quality. The SNR and contrast-to-noise ratio (CNR) were calculated, and qualitative evaluations were independently conducted by 2 neuroradiologists. After exploring the optimal AF, sample images were obtained from 1 patient by using both optimized sequences. RESULTS: Quantitatively, the CNR of the CS-AI protocol for CE 3D-T1WI and CE 3D-FLAIR sequences was superior to that of the CS protocol under the same AF (P < .05). Compared with reference CS6, the CS-AI groups had higher CNR values (all P < .05), with the CS-AI10 scan having the highest value. The SNR of the CS-AI group was better than that of the reference for both CE 3D-T1WI and CE 3D-FLAIR sequences (all P < .05). Qualitatively, the CS-AI protocol produced higher image quality scores than did the CS protocol with the same AF (all P < .05). In contrast to the reference CS6, the CS-AI group showed good image quality scores until an AF of up to 10 (all P < .05). The CS-AI10 scan provided the optimal images, improving the delineation of normal gray-white matter boundaries and lesion areas (P < .05). Compared with the reference, CS-AI10 showed reductions in scan time of 39.25% and 39.93% for CE 3D-T1WI and CE 3D-FLAIR sequences, respectively. CONCLUSIONS: CE 3D-T1WI and CE 3D-FLAIR sequences reconstructed with CS-AI for the detection of BM may provide a more effective alternative reconstruction approach than CS. CS-AI10 is suitable for clinical applications, providing optimal image quality and a shortened scan time.
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Brain Neoplasms , White Matter , Humans , Artificial Intelligence , Brain Neoplasms/diagnostic imaging , Magnetic Resonance Imaging/methods , Gray Matter , Imaging, Three-DimensionalABSTRACT
BACKGROUND: Serum creatinine (Scr) may be not suited to timely and accurately reflect kidney injury related to chronic liver disease. Currently, the ability of arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) sequences to evaluate renal blood flow (RBF) and blood oxygen in chronic liver disease remains to be verified. PURPOSE: To investigate the value of ASL and BOLD imaging in evaluating hemodynamics and oxygenation changes during kidney injury in an animal model of chronic liver disease. STUDY TYPE: Prospective. ANIMAL MODEL: Chronic liver disease model was established by subcutaneous injection of carbon tetrachloride. Forty-three male Sprague-Dawley rats (8 weeks) were divided into a pathological group (0, 2, 4, 6, 8, 12 weeks, each group: N = 6) and a continuous-scanning group (N = 7). FIELD STRENGTH/SEQUENCE: 3-T, ASL, BOLD, and T2W. ASSESSMENT: Regions of interest in the cortex (CO), outer stripe of the outer medulla (OSOM), and inner stripe of the outer medulla (ISOM) are manually delineated. The RBF and T2* values at each time point (0, 2, 4, 6, 8, 12 weeks) are measured and compared. Hematoxylin-eosin score (HE Score, damage area scoring method), alpha-smooth muscle actin (α-SMA), hypoxia-inducible factor-1alpha (HIF-1α), peritubular capillar (PTC) density, Scr, and neutrophil gelatinase-associated lipocalin were harvested. STATISTICAL TESTS: Analysis of variance, Spearman correlation analysis, Kruskal-Wallis tests, and receiver operating characteristic analysis with the area under the curve (AUC). A P-value <0.05 was considered statistically significant. RESULTS: Renal RBF and T2* values of CO, OSOM, and ISOM were significantly different from baseline. Both RBF and T2* were significantly correlated with HE Score, α-SMA, HIF-1α, and PTC density (|r| = 0.406-0.853). RBF demonstrated superior diagnostic capability in identifying severe kidney injury in this model of chronic liver disease (AUC = 0.964). DATA CONCLUSION: Imaging by ASL and BOLD may detect renal hemodynamics and oxygenation changes related to chronic liver disease early. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.
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BACKGROUND: Roux-en-Y gastric bypass (RYGB) surgery is an effective metabolic surgery against diabetes and obesity. Clinical evidence indicates that patients with severe obesity have a poor curative effect in losing weight if they suffer from leptin or its receptor deficiency, but the underlying mechanism remains elusive. Here, we investigated the effect of leptin receptor deficiency on metabolic dysfunction in db/db mice treated by RYGB surgery. METHODS: The db/db mice and their heterozygote control db/m mice were subjected to RYGB or sham surgery. Body weight, blood glucose, food intake and glucose tolerance were evaluated. Micro-PET/CT and histological analysis were performed to examine the glucose uptake of tissues and the fat changes in mice. The key factors in glucose and fatty acid metabolism were detected by western blot analysis. RESULTS: Compared with the sham group, the db/db mice in the RYGB group showed more significant weight regain after surgical recovery and improvement in hyperinsulinemia and glucose tolerance. However, the total body fat and multiple organ lipid deposition of RYGB-treated db/db mice was increased. The underlying mechanism studies suggested that the activation of AMPK regulated GLUT4 to increase glucose uptake, but AMPK could not promote fatty acid oxidation through the JAK2/STAT3 pathway under leptin receptor deficiency in db/db mice. CONCLUSION: We conclude that leptin receptor deficiency impedes the AMPK activation-mediated fat catabolism but does not affect AMPK-related glucose utilization after metabolic surgery in db/db mice. This result helps select surgical indications for patients with obesity and diabetes.
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BACKGROUND: The aim of this study was to analyse transcriptomic differences between primary and recurrent high-grade serous ovarian carcinoma (HGSOC) to identify prognostic biomarkers. METHODS: We analysed 19 paired primary and recurrent HGSOC samples using targeted RNA sequencing. We selected the best candidates using in silico survival and pathway analysis and validated the biomarkers using immunohistochemistry on a cohort of 44 paired samples, an additional cohort of 504 primary HGSOCs and explored their function. RESULTS: We identified 233 differential expressed genes. Twenty-three showed a significant prognostic value for PFS and OS in silico. Seven markers (AHRR, COL5A2, FABP4, HMGCS2, ITGA5, SFRP2 and WNT9B) were chosen for validation at the protein level. AHRR expression was higher in primary tumours (p < 0.0001) and correlated with better patient survival (p < 0.05). Stromal SFRP2 expression was higher in recurrent samples (p = 0.009) and protein expression in primary tumours was associated with worse patient survival (p = 0.022). In multivariate analysis, tumour AHRR and SFRP2 remained independent prognostic markers. In vitro studies supported the anti-tumorigenic role of AHRR and the oncogenic function of SFRP2. CONCLUSIONS: Our results underline the relevance of AHRR and SFRP2 proteins in aryl-hydrocarbon receptor and Wnt-signalling, respectively, and might lead to establishing them as biomarkers in HGSOC.
Subject(s)
Cystadenocarcinoma, Serous , Ovarian Neoplasms , Female , Humans , Prognosis , Ovarian Neoplasms/pathology , Gene Expression Profiling , Biomarkers, Tumor/genetics , Cystadenocarcinoma, Serous/pathology , Membrane Proteins/genetics , Repressor Proteins/genetics , Basic Helix-Loop-Helix Transcription Factors/geneticsABSTRACT
Clean air actions (CAAs) in China have been linked to considerable benefits in public health. However, whether the beneficial effects of CAAs are equally distributed geographically is unknown. Using high-resolution maps of the distributions of major air pollutants (fine particulate matter [PM2.5] and ozone [O3]) and population, we aimed to track spatiotemporal changes in health impacts from, and geographic inequality embedded in, the reduced exposures to PM2.5 and O3 from 2013 to 2020. We used a method established by the Global Burden of Diseases Study. By analyzing the changes in loss of life expectancy (LLE) attributable to PM2.5 and O3, we calculated the gain of life expectancy (GLE) to quantify the health benefits of the air-quality improvement. Finally, we assessed the geographic inequality embedded in the GLE using the Gini index (GI). Based on risk assessments of PM2.5 and O3, during the first stage of CAAs (2013 to 2017), the mean GLE was 1.87 months. Half of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed (GI 0.44). During the second stage of CAAs (2017 to 2020), the mean GLE increased to 3.94 months and geographic inequality decreased (GI 0.18). According to our assessments, CAAs were enhanced, from the first to second stages, in terms of not only preventing premature mortality but also ameliorating health inequalities. The enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5 and O3 levels. Our findings will contribute to optimizing future CAAs.
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OBJECTIVE@#To study on the decomposition kinetics of bupivacaine in brain, blood and urine, which were collected from dogs executed by bupivacaine and stored in different conditions.@*METHODS@#Dogs were given arachnoid cavity anesthesia with bupivacaine. Then the brain, blood and urine were collected and divided equally to three groups stored in 20, 4 and -20 degrees C respectively. The concentrations of bupivacaine at different days were determined by the GC. The equation and half-time period of decomposition kinetics were imitated and calculated with WinNolin program.@*RESULTS@#The decomposition kinetics of bupivacaine in the dogs' brain, blood and urine were fit to the first order kinetics. The common equation was lgC = lgCo-kt/2.303 and k was the decomposition constant of first order reaction.@*CONCLUSION@#Bupivacaine in the brain, blood and urine specimens were found to be decomposed at various environments for storage. The higher temperature for storage, the faster of decomposition reaction.