Search

Objective: We aimed to investigate the prevalence of covert hepatic encephalopathy (CHE) in cirrhotic patients in China and its risk factors. Methods: A multicenter prospective observational study was conducted from January 2021 to March 2022 at 16 medical centers across China to investigate the risk factors of CHE and establish a prediction model for CHE episodes. Results: A total of 528 patients were enrolled in the study. Based on both the psychometric hepatic encephalopathy score and Stroop test results, the prevalence of CHE was 50.4% (266/528), and the consistency between these two tests was 68.9%. Multivariate analysis showed that age (odds ratio [OR] 1.043, 95% confidence interval [CI] 1.022–1.063, P < 0.001), duration of education (OR 0.891, 95% CI 0.832–0.954, P = 0.001), comorbidities of cardiovascular diseases, hypertension, cerebral apoplexy or diabetes mellitus (OR 2.072, 95% CI 1.370–3.133, P < 0.001), Child–Pugh score (OR 1.142, 95% CI 1.029–1.465, P = 0.025), and blood urea nitrogen concentration (OR 1.126, 95% CI 1.038–1.221, P = 0.004) were associated with CHE episodes. According to the Chronic Liver Disease Questionnaire, CHE patients had lower scores for abdominal symptoms and systemic symptoms (P < 0.001), indicating a poor health‐related quality of life. Based on a stepwise Cox regression hazard model, we established a nomogram for determining the probabilities of CHE episodes, and the area under the receiver operating characteristic curve was 0.733 (95% CI 0.679–0.788) and 0.713 (95% CI 0.628–0.797) in the training and validation cohorts. Conclusions: CHE is a common complication of cirrhosis in China. Large‐scale studies with long‐term follow‐up are needed to determine the natural history of Chinese CHE patients. [ABSTRACT FROM AUTHOR]

Accurate estimation of regional and global patterns of ecosystem respiration (ER) is crucial to improve the understanding of terrestrial carbon cycles and the predictive ability of the global carbon budget. However, large uncertainties still exist in regional and global ER estimation due to the drawbacks of modeling methods. Based on eddy covariance ER data from 132 sites in China from 2002 to 2020, we established Intelligent Random Forest (IRF) models that integrated ecological understanding with machine learning techniques to estimate ER. The results showed that the IRF models performed better than semiempirical models and machine learning algorithms. The observed data revealed that gross primary productivity (GPP), living plant biomass, and soil organic carbon (SOC) were of great importance in controlling the spatiotemporal variability of ER across China. An optimal model governed by annual GPP, living plant biomass, SOC, and air temperature (IRF‐04 model) matched 93% of the spatiotemporal variation in site‐level ER, and was adopted to evaluate the spatiotemporal pattern of ER in China. Using the optimal model, we obtained that the annual value of ER in China ranged from 5.05 to 5.84 Pg C yr−1 between 2000 and 2020, with an average value of 5.53 ± 0.22 Pg C yr−1. In this study, we suggest that future models should integrate process‐based and data‐driven approaches for understanding and evaluating regional and global carbon budgets. Plain Language Summary: With China already committing to achieve carbon neutrality before 2060, an accurate assessment of land carbon sink and its flux rate in China is an increasingly important area in global change ecology. In this essay, a high‐efficiency and accurate simulation method was introduced in this field; This method is particularly useful in the assessment of carbon sink and its flux rate in China by combining with reliable observation flux data. Using this new method, a reliable and reasonable value of carbon flux (ecosystem respiration) was obtained. Meanwhile, that method provides a better understanding of the mechanism governing the spatiotemporal variability of carbon flux. Therefore, this present study has gone some way toward enhancing our understanding of a comprehensive assessment and analysis of land carbon sink in China. Key Points: A model integrating ecological knowledge and machine learning was established to estimate ecosystem respiration (ER) in ChinaThe spatiotemporal patterns of ER are significantly affected by productivity, plant biomass, soil organic carbon, and air temperatureChina's ER was estimated to be 5.53 ± 0.22 petagrams of carbon per year (Pg C yr−1) on average for the years 2000–2020 [ABSTRACT FROM AUTHOR]

Background: Diagnostic criteria for sarcopenia have not been established in Chinese. This study established criteria based on the L3‐skeletal muscle index (L3‐SMI) and assessed its value for outcomes predicting in cirrhotic Chinese patients. Methods: Totally 911 subjects who underwent a CT scan at two centres were enrolled in Cohort 1 (394 male and 417 female subjects, aged 20–80 years). The data of those subjects younger than 60 years (365 male and 296 female subjects) were used to determine the reference intervals of the L3‐SMI and its influencing factors. Cohort 2 consisted of 480 patients (286 male and 184 female patients) from three centres, and their data were used to investigate the prevalence of sarcopenia and evaluate the value of L3‐SMI for predicting the prognosis and complications of cirrhosis. Results: Age and sex had the greatest effects on the L3‐SMI (P < 0.001). The L3‐SMI scores were clearly higher in male patients than in female patients (52.94 ± 8.41 vs. 38.91 ± 5.65 cm2/m2, P < 0.001) and sharply declined in subjects aged ≥ 60 years. Based on the mean −1.28 × SD among adults aged < 60 years, the L3‐SMI cut‐off value for sarcopenia was 44.77 cm2/m2 in male patients and 32.50 cm2/m2 in female patients. Using these values, 22.5% of the cirrhotic patients (28.7% of male patients and 11.9% of female patients) were diagnosed with sarcopenia. Compared with non‐sarcopenia individuals, sarcopenia patients had lower body mass index (21.28 ± 3.01 vs. 24.09 ± 3.39 kg/m2, P < 0.001) and serum albumin levels (31.54 ± 5.93 vs. 32.93 ± 5.95 g/L, P = 0.032), longer prothrombin times (16.39 ± 3.05 vs. 15.71 ± 3.20 s, P = 0.049), higher total bilirubin concentrations (41.33 ± 57.38 vs. 32.52 ± 31.48 μmol/L, P = 0.039), worse liver function (Child–Pugh score, 8.05 ± 2.11 vs. 7.32 ± 2.05, P = 0.001), higher prevalence of cirrhosis‐related complications (81.82% vs. 62.24%, P < 0.001) and mortality (30.68% vs. 11.22%, P < 0.001). Overall survival was significantly lower in the sarcopenia group [risk ratio (RR) = 2.643, 95% confidence interval (CI) 1.646–4.244, P < 0.001], accompanied with an increased cumulative incidence of ascites (RR = 1.827, 95% CI 1.259–2.651, P = 0.002), spontaneous bacterial peritonitis (RR = 3.331, 95% CI 1.404–7.903, P = 0.006), hepatic encephalopathy (RR = 1.962, 95% CI 1.070–3.600, P = 0.029), and upper gastrointestinal varices (RR = 2.138, 95% CI 1.319–3.466, P = 0.002). Subgroup analysis showed sarcopenia shortened the survival of the patients with Model For End‐Stage Liver Disease score > 14 (RR = 4.310, 95% CI 2.091–8.882, P < 0.001) or Child–Pugh C (RR = 3.081, 95% CI 1.516–6.260, P = 0.002). Conclusions: Sarcopenia is a common comorbidity of cirrhosis and can be used to predict cirrhosis‐related complications and the prognosis. [ABSTRACT FROM AUTHOR]

Background and Aim: Considering the large size of the potential population and limitations of common detection methods, covert hepatic encephalopathy (CHE) is difficult to screen for routinely. The present study aims to explore EncephalApp Stroop Test as a smartphone‐based CHE screening tool in China. Methods: A multicenter, single‐visit study was carried out. The cutoff of the Chinese EncephalApp translation was determined by using Chinese standardized psychometric hepatic encephalopathy score (PHES) in cirrhotic patients as the gold standard. Indicators reflecting time required and number of tests on subtask on (naming the color of pound signs) and off (naming the color of the word in discordant coloring) were recorded, with the feedback from investigators and patients. Results: One hundred forty‐four patients were included; 58 (40.28%) patients were diagnosed with CHE by PHES. The cutoff of > 97.34 s for off time and > 186.63 s for on time + off time had the maximum area under the curve values (0.77) in all patients. Furthermore, with the cutoff of 186.63 s, on time + off time has the highest sensitivity (0.86). However, the specificity was unsatisfactory (0.59). Age and alcoholic hepatitis (odds ratio = 1.05 and 3.12, both P < 0.05) were positively correlated with the risk of CHE. The experience with electronic devices and education duration were negatively correlated (odds ratio = 0.21 and 0.92, both P < 0.05). Compared with PHES, EncephalApp represented 38% time saving. Furthermore, it was superior to PHES regarding accessibility, convenience, and acceptability by administrators (all P < 0.05). Conclusions: The EncephalApp Stroop Test is an efficient screening tool for CHE in Chinese cirrhotic patients. [ABSTRACT FROM AUTHOR]

Moso bamboos ( Phyllostachys edulis) are important forestry plants in southern China, with substantial roles to play in regional economic and ecological systems. Mixing broad-leaved forests and moso bamboos is a common management practice in China, and it is fundamental to elucidate the interactions between broad-leaved trees and moso bamboos for ensuring the sustainable provision of ecosystem services. We examine how the proportion of broad-leaved forest in a mixed managed zone, topology, and soil profile affects the effective productivity of moso bamboos (i.e., those with significant economic value), using linear regression and generalized additive models. Bamboo's diameter at breast height follows a Weibull distribution. The importance of these variables to bamboo productivity is, respectively, slope (25.9%), the proportion of broad-leaved forest (24.8%), elevation (23.3%), gravel content by volume (16.6%), slope location (8.3%), and soil layer thickness (1.2%). Highest productivity is found on the 25° slope, with a 600-m elevation, and 30% broad-leaved forest. As such, broad-leaved forest in the upper slope can have a strong influence on the effective productivity of moso bamboo, ranking only after slope and before elevation. These factors can be considered in future management practice. [ABSTRACT FROM AUTHOR]