Propofol EC50 for inducing loss of consciousness in patients under combined epidural-general anesthesia or general anesthesia alone: a randomized double-blind study

BackgroundCombined epidural-general anesthesia (GA + EA) has been recommended as a preferred technique for both thoracic and abdominal surgery. The epidural anesthesia on the general anesthetic (GA) requirements has not been well investigated. Therefore, we conducted the present study to explore the predicted effect-site concentration of propofol (Ceprop) required for achieving the loss of consciousness (LOC) in 50% of patients (EC50) with or without epidural anesthesia.MethodsSixty patients scheduled for gastrectomy were randomized into the GA + EA group or GA alone group to receive general anesthesia alone. Ropivacaine 0.375% was used for epidural anesthesia to achieve a sensory level of T4 or above prior to the induction of general anesthesia. The EC50 of predicted Ceprop for LOC was determined by the up–down sequential method. The consumption of anesthetics, emergence time from anesthesia, and postoperative outcomes were also recorded and compared.ResultsThe EC50 of predicted Ceprop for LOC was lower in the GA + EA group than in the GA alone group [2.97 (95% CI: 2.63–3.31) vs. 3.36 (95% CI: 3.19–3.53) μg mL−1, (p = 0.036)]. The consumption of anesthetics was lower in the GA + EA group than in the GA alone group (propofol: 0.11 ± 0.02 vs. 0.13 ± 0.02 mg kg−1 min−1, p = 0.014; remifentanil: 0.08 ± 0.03 vs. 0.14 ± 0.04 μg kg−1 min−1, p < 0.001). The emergence time was shorter in the GA + EA group than in the GA alone group (16.0 vs. 20.5 min, p = 0.013).ConclusionConcomitant epidural anesthesia reduced by 15% the EC50 of predicted Ceprop for LOC, decreased the consumptions of propofol and remifentanil during maintenance of anesthesia, and fastened recovery from anesthesia.Clinical trial registrationClinicalTrials.gov, identifier: NCT05124704

Optimization of urban mini-bus stop spacing: a case study of Shanghai (China)

U posljednjih se nekoliko godina služba mini-autobusa brzo razvija, a odgovarajući razmak između stajališta značajno poboljšava učinkovitost putovanja stanovnika. Kako bi mini-bus stajališta bila praktično locirana, u ovom se radu najprije predlaže matematički model temeljen na Voronoi dijagramima u svrhu smanjenja ukupnog vremena putovanja putnika. Za rješenje tog modela primijenjena je poboljšana tehnika Wilson-Han-Powell sekvencionalno kvadratno programiranje (SQP). Na temelju geografskih informacijskih sustava (GIS) korišten je Kartezijanski koordinatni sustav za izračunavanje pješačke udaljenosti između mini-bus stanica i početnih ili odredišta, koja se ne mogu izravno izmjeriti. Drugo, u skladu sa stvarnim stanjem, u radu se predlažu metode modifikacije za podešavanje stajališta mini-autobusa. Valjanost i korisnost metodologije ispitana je njenom primjenom na stvarnom slučaju u Šangaju (Kina). Rezultati proračuna pokazuje da se modelom dobro rješava problem određivanja razmaka između stajališta mini autobusa.In recent years, the mini-bus service has gained a rapid development, while the reasonable stop spacing is significant to improve residents’ travel efficiency. In order to locate the mini-bus stops practically, this paper firstly proposes a mathematical model based on Voronoi Diagrams to minimize residents’ total travel time. Improved Wilson-Han-Powell Sequential Quadratic Programming (SQP) technique is employed to solve the model. Based on Geographic Information Systems (GIS), the Cartesian coordinate system is used to calculate the walking distance between mini-bus stops and origins or destinations, which cannot be directly measured. Secondly, based on the actual situation, this paper proposes modification methods for adjusting mini-bus stops. The validity and usefulness of the methodology is tested through applying it to a real case in Shanghai (China). The calculation results suggest that the model deals well with the mini-bus stop spacing problem

Finding the best predictive model for hypertensive depression in older adults based on machine learning and metabolomics research

ObjectiveDepression is a common comorbidity in hypertensive older adults, yet depression is more difficult to diagnose correctly. Our goal is to find predictive models of depression in hypertensive patients using a combination of various machine learning (ML) methods and metabolomics.MethodsMethods We recruited 379 elderly people aged ≥65 years from the Chinese community. Plasma samples were collected and assayed by gas chromatography/liquid chromatography-mass spectrometry (GC/LC-MS). Orthogonal partial least squares discriminant analysis (OPLS-DA), volcano diagrams and thermograms were used to distinguish metabolites. The attribute discriminators CfsSubsetEval combined with search method BestFirst in WEKA software was used to find the best predicted metabolite combinations, and then 24 classification methods with 10-fold cross-validation were used for prediction.Results34 individuals were considered hypertensive combined with depression according to our criteria, and 34 subjects with hypertension only were matched according to age and sex. 19 metabolites by GC-MS and 65 metabolites by LC-MS contributed significantly to the differentiation between the depressed and non-depressed cohorts, with a VIP value of more than 1 and a P value of less than 0.05. There were multiple metabolic pathway alterations. The metabolite combinations screened with WEKA for optimal diagnostic value included 12 metabolites. The machine learning methods with AUC values greater than 0.9 were bayesNet and random forests, and their other evaluation measures are also better.ConclusionAltered metabolites and metabolic pathways are present in older adults with hypertension combined with depression. Methods using metabolomics and machine learning performed quite well in predicting depression in hypertensive older adults, contributing to further clinical research

Discovery of potential biomarkers for osteoporosis using LC/GC−MS metabolomic methods

PurposeFor early diagnosis of osteoporosis (OP), plasma metabolomics of OP was studied by untargeted LC/GC−MS in a Chinese elderly population to find possible diagnostic biomarkers.MethodsA total of 379 Chinese community-dwelling older adults aged ≥65 years were recruited for this study. The BMD of the calcaneus was measured using quantitative ultrasound (QUS), and a T value ≤-2.5 was defined as OP. Twenty-nine men and 47 women with OP were screened, and 29 men and 36 women were matched according to age and BMI as normal controls using propensity matching. Plasma from these participants was first analyzed by untargeted LC/GC−MS, followed by FC and P values to screen for differential metabolites and heatmaps and box plots to differentiate metabolites between groups. Finally, metabolic pathway enrichment analysis of differential metabolites was performed based on KEGG, and pathways with P ≤ 0.05 were selected as enrichment pathways.ResultsWe screened metabolites with FC>1.2 or FC<1/1.2 and P<0.05 and found 33 differential metabolites in elderly men and 30 differential metabolites in elderly women that could be potential biomarkers for OP. 2-Aminomuconic acid semialdehyde (AUC=0.72, 95% CI 0.582-0.857, P=0.004) is highly likely to be a biomarker for screening OP in older men. Tetradecanedioic acid (AUC=0.70, 95% CI 0.575-0.818, P=0.004) is highly likely to be a biomarker for screening OP in older women.ConclusionThese findings can be applied to clinical work through further validation studies. This study also shows that metabolomic analysis has great potential for application in the early diagnosis and recurrence monitoring of OP in elderly individuals

Characterizing China's road network development from a spatial entropy perspective

Understanding the spatial characteristics of road networks is crucial for the planning of road networks. Although road networks have been frequently evaluated in combination with various socioeconomic factors, the current road network development in developing countries still needs to be better understood. Combining road network density and spatial entropy for 2728 counties in China, we provide a comprehensive assessment of road networks and their key influencing factors. Our results indicate a significant spatial heterogeneity of the road network development, especially on both sides of the Heihe-Tengchong line. Demographic-economic and topographic variables jointly explained 54.2% and 65.1% of the spatial variations in road network density and entropy, respectively. Road entropy increases with road network density in line with a saturation curve from provincial to national scales, which offers guidance for future road planning. Using a K-means clustering analysis, we categorized China's road networks into four groups corresponding to the development stages. Our findings improve the current understanding of road network development in China and provide important implications for national road network planning in the future.This work was supported by the National Natural Science Foundation of China (31988102

Updated estimation of forest biomass carbon pools in China, 1977-2018

China is one of the major forest countries in the world, and the accurate estimation of its forest biomass carbon (C) pool is critical for evaluating the country's C budget and ecosystem services of forests. Although several studies have estimated China's forest biomass using national forest inventory data, most of them were limited to the period of 2004-2008. In this study, we extended our estimation to the most recent period of 2014-2018. Using datasets of eight inventory periods from 1977 to 2018 and the continuous biomass expansion factor method, we estimated that the total biomass C pool and average biomass C density in Chinese forests increased from 4717 Tg C (1 Tg = 10(12) g) in the period of 1977-1981 to 7975 Tg C in the period of 2014-2018 and 38.2 Mg C ha(-1) to 45.8 Mg C ha(-1) (1 Mg = 10(6) g), respectively, with a net increase of 3258 Tg C and an annual sink of 88.0 Tg C yr(-1) . Over the most recent 10 years (20092018), the average national forest biomass C density and C sink were 44.6 Mg C ha(-1) and 154.8 Tg C yr(-1) , respectively, much larger than those of 39.6 Mg C ha(-1) and 63.3 Tg C yr(-1) in the period 1977-2008. These pronounced increases were largely attributed to afforestation practices, forest growth, and environmental changes. Our results have documented the importance of ecological restoration practices, provided an essential basis for assessing ecosystem services, and helped to achieve China's C neutrality target

Little evidence that Amazonian rainforests are approaching a tipping point

The resilience of the Amazon rainforest to climate and land-use change is crucial for biodiversity, regional climate and the global carbon cycle. Deforestation and climate change, via increasing dry-season length and drought frequency, may already have pushed the Amazon close to a critical threshold of rainforest dieback. Here, we quantify changes of Amazon resilience by applying established indicators (for example, measuring lag-1 autocorrelation) to remotely sensed vegetation data with a focus on vegetation optical depth (1991-2016). We find that more than three-quarters of the Amazon rainforest has been losing resilience since the early 2000s, consistent with the approach to a critical transition. Resilience is being lost faster in regions with less rainfall and in parts of the rainforest that are closer to human activity. We provide direct empirical evidence that the Amazon rainforest is losing resilience, risking dieback with profound implications for biodiversity, carbon storage and climate change at a global scale.The Amazon rainforest is increasingly under pressure from climate change and deforestation. The resilience of three-quarters of the forest, particularly in drier areas or close to human activity, has been decreasing since the 2000s, indicating that the system may be approaching a tipping point

The association between visceral fat obesity and prefrailty in Chinese older adults: a cross-sectional study

Abstract Background The prevalence of obesity is escalating. Previous research has concentrated on the link between frailty and obesity; however, the association between prefrailty and obesity has been less studied. Prefrailty screening and intervention may prevent or postpone frailty in older persons. Objective The study was to investigate into the relationship between prefrailty and several obesity indicators in Chinese community-dwelling older individuals. Methods This research employed the Frailty Screening Index to investigate the frailty phenotype of people living in Shanghai. Bioelectrical impedance analysis was used for evaluating body composition. Results There were 510 participants (39.0%) with high visceral adipose areas. Participants with a high visceral adipose area showed a higher risk of prefrailty (adjusted OR, 1.53; 95% CI, 1.19–1.96), according to multivariate models. When body mass index (BMI) and visceral fat area (VFA) were combined, it was discovered that having an overweight BMI with normal VFA was a protective factor for prefrailty (corrected OR, 0.62; 95% CI, 0.43–0.90), but having a normal weight but excess VFA increased the risk of prefrailty (corrected OR, 1.87; 95% CI, 1.15–3.03). Conclusion Visceral fat obesity is an independent risk factor for prefrailty in Chinese older adults. Implementing targeted interventions, such as dietary modifications, increased physical activity, and other lifestyle changes, could play a crucial role in reducing the risk of prefrailty and improving overall health outcomes in this population