Aim
Childhood obesity is a major public problem worldwide, and sleep duration may be associated with childhood obesity. We conducted a systematic review and meta‐analysis of prospective cohort ...studies to estimate the associations between sleep duration and obesity/body mass index (BMI) in children.
Methods
PubMed, Embase and the Cochrane Library were searched. For the meta‐analysis, the pooled relative risk (RR) and 95% confidence intervals (CI) were estimated to reveal the association between short sleep duration and obesity. For the review, the outcomes focused on BMI change or subsequent BMI status.
Results
A total of 12 studies (15 populations) met the criteria for inclusion in the meta‐analysis. Short sleep duration was significantly associated with obesity (RR: 1.45; 95% CI: 1.14–1.85). After excluding two cohorts that substantially affected the heterogeneity, the pooled results remained significant (RR: 1.30; 95% CI: 1.20–1.42), and the association was not substantially altered in the subgroup analysis. In addition, we summarised 24 studies that met the criteria for our review of the relationship between sleeping and BMI.
Conclusion
The present meta‐analysis indicated that short sleep duration increased the risk of childhood obesity. Public health efforts that encourage children to have sufficient sleep time may be important in combating obesity.
Histone deacetylase 6 in cancer Li, Ting; Zhang, Chao; Hassan, Shafat ...
Journal of hematology & oncology,
09/2018, Volume:
11, Issue:
1
Journal Article
Peer reviewed
Open access
Histone acetylation and deacetylation are important epigenetic mechanisms that regulate gene expression and transcription. Histone deacetylase 6 (HDAC6) is a unique member of the HDAC family that not ...only participates in histone acetylation and deacetylation but also targets several nonhistone substrates, such as α-tubulin, cortactin, and heat shock protein 90 (HSP90), to regulate cell proliferation, metastasis, invasion, and mitosis in tumors. Furthermore, HDAC6 also upregulates several critical factors in the immune system, such as program death receptor-1 (PD-1) and program death receptor ligand-1 (PD-L1) receptor, which are the main targets for cancer immunotherapy. Several selective HDAC6 inhibitors are currently in clinical trials for cancer treatment and bring hope for patients with malignant tumors. A fuller understanding of HDAC6 as a critical regulator of many cellular pathways will help further the development of targeted anti-HDAC6 therapies. Here, we review the unique features of HDAC6 and its role in cancer, which make HDAC6 an appealing drug target.
•The proposed method introduces the deterministic policy into the generative adversarial imitation learning method, so that the robot can quickly imitate the demonstration policy without reward ...engineering.•Drawing on the idea of learning from demonstration (LfD), the method inputs the demonstration data both into the generator and the discriminator in order to improve the stability of training process by leveraging from the demonstration data rather than simply from the exploration data.
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This paper proposes a deterministic generative adversarial imitation learning method which allows the robot to implement the motion planning task rapidly by learning from the demonstration data without reward function. In our method, the deep deterministic policy gradient method is used as the generator for learning the action policy on the basis of discriminator, and the demonstration data is input into the generator to ensure its stability. Three experiments on the push and pick-and-place tasks are conducted in the gym robotic environment. Results show that the learning speed of our method is much faster than the stochastic generative adversarial imitation learning method, and it can effectively learn from the demonstration data in different states of the task with higher learning stability. The proposed method can complete the motion planning task without environmental reward quickly and improve the stability of the training process.
The incidence of thyroid cancer is rising steadily because of overdiagnosis and overtreatment conferred by widespread use of sensitive imaging techniques for screening. This overall incidence growth ...is especially driven by increased diagnosis of indolent and well-differentiated papillary subtype and early-stage thyroid cancer, whereas the incidence of advanced-stage thyroid cancer has increased marginally. Thyroid ultrasound is frequently used to diagnose thyroid cancer. The aim of this study was to use deep convolutional neural network (DCNN) models to improve the diagnostic accuracy of thyroid cancer by analysing sonographic imaging data from clinical ultrasounds.
We did a retrospective, multicohort, diagnostic study using ultrasound images sets from three hospitals in China. We developed and trained the DCNN model on the training set, 131 731 ultrasound images from 17 627 patients with thyroid cancer and 180 668 images from 25 325 controls from the thyroid imaging database at Tianjin Cancer Hospital. Clinical diagnosis of the training set was made by 16 radiologists from Tianjin Cancer Hospital. Images from anatomical sites that were judged as not having cancer were excluded from the training set and only individuals with suspected thyroid cancer underwent pathological examination to confirm diagnosis. The model's diagnostic performance was validated in an internal validation set from Tianjin Cancer Hospital (8606 images from 1118 patients) and two external datasets in China (the Integrated Traditional Chinese and Western Medicine Hospital, Jilin, 741 images from 154 patients; and the Weihai Municipal Hospital, Shandong, 11 039 images from 1420 patients). All individuals with suspected thyroid cancer after clinical examination in the validation sets had pathological examination. We also compared the specificity and sensitivity of the DCNN model with the performance of six skilled thyroid ultrasound radiologists on the three validation sets.
Between Jan 1, 2012, and March 28, 2018, ultrasound images for the four study cohorts were obtained. The model achieved high performance in identifying thyroid cancer patients in the validation sets tested, with area under the curve values of 0·947 (95% CI 0·935–0·959) for the Tianjin internal validation set, 0·912 (95% CI 0·865–0·958) for the Jilin external validation set, and 0·908 (95% CI 0·891–0·925) for the Weihai external validation set. The DCNN model also showed improved performance in identifying thyroid cancer patients versus skilled radiologists. For the Tianjin internal validation set, sensitivity was 93·4% (95% CI 89·6–96·1) versus 96·9% (93·9–98·6; p=0·003) and specificity was 86·1% (81·1–90·2) versus 59·4% (53·0–65·6; p<0·0001). For the Jilin external validation set, sensitivity was 84·3% (95% CI 73·6–91·9) versus 92·9% (84·1–97·6; p=0·048) and specificity was 86·9% (95% CI 77·8–93·3) versus 57·1% (45·9–67·9; p<0·0001). For the Weihai external validation set, sensitivity was 84·7% (95% CI 77·0–90·7) versus 89·0% (81·9–94·0; p=0·25) and specificity was 87·8% (95% CI 81·6–92·5) versus 68·6% (60·7–75·8; p<0·0001).
The DCNN model showed similar sensitivity and improved specificity in identifying patients with thyroid cancer compared with a group of skilled radiologists. The improved technical performance of the DCNN model warrants further investigation as part of randomised clinical trials.
The Program for Changjiang Scholars and Innovative Research Team in University in China, and National Natural Science Foundation of China.
Genetic variants and lifestyle factors have been associated with gastric cancer risk, but the extent to which an increased genetic risk can be offset by a healthy lifestyle remains unknown. We aimed ...to establish a genetic risk model for gastric cancer and assess the benefits of adhering to a healthy lifestyle in individuals with a high genetic risk.
In this meta-analysis and prospective cohort study, we first did a fixed-effects meta-analysis of the association between genetic variants and gastric cancer in six independent genome-wide association studies (GWAS) with a case-control study design. These GWAS comprised 21 168 Han Chinese individuals, of whom 10 254 had gastric cancer and 10 914 geographically matched controls did not. Using summary statistics from the meta-analysis, we constructed five polygenic risk scores in a range of thresholds (p=5 × 10−4 p=5 × 10−5 p=5 × 10−6 p=5 × 10−7, and p=5 × 10−8) for gastric cancer. We then applied these scores to an independent, prospective, nationwide cohort of 100 220 individuals from the China Kadoorie Biobank (CKB), with more than 10 years of follow-up. The relative and absolute risk of incident gastric cancer associated with healthy lifestyle factors (defined as not smoking, never consuming alcohol, the low consumption of preserved foods, and the frequent intake of fresh fruits and vegetables), was assessed and stratified by genetic risk (low quintile 1 of the polygenic risk score, intermediate quintile 2–4 of the polygenic risk score, and high quintile 5 of the polygenic risk score). Individuals with a favourable lifestyle were considered as those who adopted all four healthy lifestyle factors, those with an intermediate lifestyle adopted two or three factors, and those with an unfavourable lifestyle adopted none or one factor.
The polygenic risk score derived from 112 single-nucleotide polymorphisms (p<5 × 10−5) showed the strongest association with gastric cancer risk (p=7·56 × 10−10). When this polygenic risk score was applied to the CKB cohort, we found that there was a significant increase in the relative risk of incident gastric cancer across the quintiles of the polygenic risk score (ptrend<0·0001). Compared with individuals who had a low genetic risk, those with an intermediate genetic risk (hazard ratio HR 1·54 95% CI 1·22–1·94, p=2·67 × 10−4) and a high genetic risk (2·08 1·61–2·69, p<0·0001) had a greater risk of gastric cancer. A similar increase in the relative risk of incident gastric cancer was observed across the lifestyle categories (ptrend<0·0001), with a higher risk of gastric cancer in those with an unfavourable lifestyle than those with a favourable lifestyle (2·03 1·46–2·83, p<0·0001). Participants with a high genetic risk and a favourable lifestyle had a lower risk of gastric cancer than those with a high genetic risk and an unfavourable lifestyle (0·53 0·29–0·99, p=0·048), with an absolute risk reduction of 1·12% (95% CI 0·62–1·56).
Chinese individuals at an increased risk of incident gastric cancer could be identified by use of our newly developed polygenic risk score. Compared with individuals at a high genetic risk who adopt an unhealthy lifestyle, those who adopt a healthy lifestyle could substantially reduce their risk of incident gastric cancer.
National Key R&D Program of China, National Natural Science Foundation of China, 333 High-Level Talents Cultivation Project of Jiangsu Province, and China Postdoctoral Science Foundation.
Multifunctional hydrogels with high electrical conductivity and mechanical flexibility are widely used as flexible strain sensors in different fields such as artificial intelligence, electronics and ...flexible sensing. However, when the temperature drops below the freezing point, the solidification of water leads to solidify or even failure of the hydrogel, severely limiting the application in low temperature environments. Thus, the hydrogel was prepared by a freeze-thaw method using polyvinyl alcohol, polyvinylpyrolidone, sodium chloride, glycerol and sodium carboxymethyl cellulose. The hydrogel exhibited excellent electrical conductivity and mechanical property in −40 °C–20 °C. Simultaneously, the hydrogel sensor possessed prominent sensitivity and cyclic stability to accurately monitor human motion in real time, including large-scale human motion such as wrist, elbow, and knee flexion movements as well as subtle human motion. There were no adverse reactions after the hydrogel into mice during14 days, indicating good biocompatibility of the hydrogel. Furthermore, the hydrogel could be printed in different shapes by 3D printing. The investigation provides a new route for the development of multi-functional hydrogel wearable sensors.
The hydrogel exhibited concurrently enhanced mechanical property, freezing resistance, water retention ability and biocompatibility by introducing Sodium carboxymethyl cellulose, which could serve as wearable sensor for monitoring human motions. Display omitted
•Hydrogels exhibited anti-freezing and water retention and biocompatibility.•Sodium carboxymethyl cellulose possesses biocompatibility and biodegradability.•Hydrogel sensor can detect the movement characteristics of various human joints.•Hydrogel no adverse reactions after the hydrogel into mice during14 days.
The Gail model has been widely used and validated with conflicting results. The current study aims to evaluate the performance of different versions of the Gail model by means of systematic review ...and meta-analysis with trial sequential analysis (TSA).
Three systematic review and meta-analyses were conducted. Pooled expected-to-observed (E/O) ratio and pooled area under the curve (AUC) were calculated using the DerSimonian and Laird random-effects model. Pooled sensitivity, specificity and diagnostic odds ratio were evaluated by bivariate mixed-effects model. TSA was also conducted to determine whether the evidence was sufficient and conclusive.
Gail model 1 accurately predicted breast cancer risk in American women (pooled E/O = 1.03; 95% CI 0.76-1.40). The pooled E/O ratios of Caucasian-American Gail model 2 in American, European and Asian women were 0.98 (95% CI 0.91-1.06), 1.07 (95% CI 0.66-1.74) and 2.29 (95% CI 1.95-2.68), respectively. Additionally, Asian-American Gail model 2 overestimated the risk for Asian women about two times (pooled E/O = 1.82; 95% CI 1.31-2.51). TSA showed that evidence in Asian women was sufficient; nonetheless, the results in American and European women need further verification. The pooled AUCs for Gail model 1 in American and European women and Asian females were 0.55 (95% CI 0.53-0.56) and 0.75 (95% CI 0.63-0.88), respectively, and the pooled AUCs of Caucasian-American Gail model 2 for American, Asian and European females were 0.61 (95% CI 0.59-0.63), 0.55 (95% CI 0.52-0.58) and 0.58 (95% CI 0.55-0.62), respectively. The pooled sensitivity, specificity and diagnostic odds ratio of Gail model 1 were 0.63 (95% CI 0.27-0.89), 0.91 (95% CI 0.87-0.94) and 17.38 (95% CI 2.66-113.70), respectively, and the corresponding indexes of Gail model 2 were 0.35 (95% CI 0.17-0.59), 0.86 (95% CI 0.76-0.92) and 3.38 (95% CI 1.40-8.17), respectively.
The Gail model was more accurate in predicting the incidence of breast cancer in American and European females, while far less useful for individual-level risk prediction. Moreover, the Gail model may overestimate the risk in Asian women and the results were further validated by TSA, which is an addition to the three previous systematic review and meta-analyses.
PROSPERO CRD42016047215 .
Chinese urbanization has drawn widespread attention since the 21st century. Understanding urban expansion at a watershed scale including cities of different sizes is important for improving our ...current knowledge of the urban extent and its impact on the hydrological cycle, water management, surface energy balances, and biodiversity. Impervious surface area (ISA) can be used as a synthesized quantifiable index to reflect the intensity of natural ecosystems changing into urban ecosystems. It is important to understand ISA patterns and characteristics, which requires long-term impervious surface data at a high spatial and temporal resolution. Previous methods of ISA estimation mainly focused on the spectral differences between ISA and other land covers, and most studies were inclined to use one or a few images without fully considering the long time series of the temporal domain of the reflective data on remote-sensing images. This assessed the Dianchi Lake watershed as a case study area to illustrate ISA change characteristics in the context of natural and cultural conditions. Firstly, more than two hundred Landsat images (from 1988 to 2017) were downloaded through the United States Geological Survey (USGS) online portal. Secondly, the improved normalized difference build-up index (INDBI) and linear spectral mixture analysis (LSMA) algorithm were combined to apply the method to a series of ISA maps of the Dianchi Lake watershed at an annual resolution. Thirdly, ISA extent characteristics of the Dianchi Lake watershed were analysed from trend and pattern aspects. The results show that the proposed method was highly reliable for detecting and characterizing change, with an extracted ISA accuracy of 92.51%, based on a sample of independent validation points. The Dianchi Lake watershed has begun to adopt 'Rashly Advancing' and 'Great Leap Forward' strategies of urbanization.
Using the historical simulations from 27 models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and 27 models in phase 6 (CMIP6), the authors evaluated the differences between CMIP5 ...and CMIP6 models in simulating the climate mean of extreme temperature over China through comparison with observations during 1979-2005. The CMIP6 models reproduce well the spatial distribution of annual maxima of daily maximum temperature (TXx), annual minima of daily minimum temperature (TNn), and frost days (FD). The model spread in CMIP6 is reduced relative to CMIP5 for some temperature indices, such as TXx, warm spell duration index (WSDI), and warm days (TX90p). The multimodel median ensembles also capture the observed trend of extreme temperature. However, the CMIP6 models still have low skill in capturing TX90p and cold nights (TN10p) and have obvious cold biases or warm biases over the Tibetan Plateau. The ability of individual models varies for different indices, although some models outperform the others in terms of the average of all indices considered for different models. By comparing different version models from the same organization, the updated CMIP6 models show no significant difference from their counterparts from CMIP5 for some models. Compared with individual models, the median ensembles show better agreement with the observations for temperature indices and their means.
Although China has eliminated absolute poverty, the effects of sickness still pose a threat to the prospect of returning to poverty in western rural areas. However, poverty governance extends beyond ...solving absolute poverty, and should enhance the family's ability to resist risks, proactively identify the existence of risks, and facilitate preventive measures to reduce the probability of falling into poverty again. This study aimed to assess the health poverty vulnerability of rural households in western China and decompose its determinants.
Based on survey data from 2022, the three-stage feasible generalized least squares method was used to calculate the health poverty vulnerability index. Then, Anderson's health behavior theory model was extended to analyse various influencing factors using binary logistic regression, and the contribution of each influencing factor was decomposed using the Shapley index. Finally, Tobit regression and the censored least absolute deviations estimation (clad) method were used to test the model's robustness.
A total of 5455 families in the rural Ningxia region of western China were included in the study. The health poverty vulnerability index of the sample population in 2022 was 0.3000 ± 0.2223, and families with vulnerability ≥0.5 accounted for 16.9% of the sample population. From the Anderson behavioral model, the three models including propensity, enabling, and demand factors had the best fit, and the AIC and BIC values were the smallest. The Shapley decomposition showed that the dimensions of the propensity factor, number of residents, age and educational level of the household head, and dependency ratio were the most important factors influencing vulnerability to health poverty. Tobit regression and the clad method proved the reliability of the constructed model through a robustness test.
Rural areas still face the risk of becoming poor or falling into poverty owing to residents' health problems. Health poverty alleviation should gradually change from a focus on treatment to prevention, and formulate a set of accurate and efficient intervention policies from a forward-looking perspective to consolidate the results of health poverty alleviation and prevent widescale poverty return.
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