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Background The prevalence of comorbidity in the elderly is showing a rising trend year by year with the acceleration of population aging. Comorbidity is a key risk factor for frailty in the elderly. Then frailty only increases the risk of adverse health outcomes for patients with comorbidity, but also significantly increases their family medical expenses. It has a certain guiding value for the management of comorbidity to identify the frailty conditions of elderly patients with comorbidity as early as possible. Objective To systematically review the prevalence of frailty in elderly patients with comorbidity. Methods CNKI, VIP, CBM, WanFang, PubMed, EmBase, Web of Science and Cochrane Library were searched in December 2021 for the investigation studies on the current status of frailty in elderly patients with comorbidity published from inception to December 4, 2021. Two researchers performed literature screening and data extraction independently. The cross-sectional study quality rating scale and Newcastle-Ottawa Scale (NOS) recommended by Agency for Healthcare Research and Quality (AHRQ) were used to assess the risk of bias of the included studies and Stata 14.0 was adopted for meta-analysis. Results A total of 25 studies involving 16 062 elderly patients with comorbidity were included. Meta-analysis results showed that the prevalence of frailty and pre-frailty in elderly patients with comorbidity was 26.7%〔95%CI (21.9%, 31.5%) 〕and 47.7%〔95%CI (43.9%, 51.4%) 〕. Subgroup analysis showed that the prevalence of frailty in older adults with≥2, ≥3, ≥4, and≥5 chronic diseases was 25.1%〔95%CI (19.3%, 30.8%) 〕, 27.4%〔95%CI (13.7%, 41.0%) 〕, 60.7%〔95%CI (29.0%, 92.4%) 〕, and 23.5%〔95%CI (8.6%, 38.5%) 〕, respectively. The prevalence of frailty in elderly patients with comorbidity in Oceania (52.1%) and Asia (31.3%) were significantly higher than Europe (16.9%) and South America (13.2%) . The prevalence of frailty in elderly patients with comorbidity in hospital (26.2%) was significantly higher than community (23.2%) . The prevalence of frailty in elderly patients with comorbidity screened by Clinical Frailty Scale (CFS) , Fried frailty phenotype scale and FRAIL Scale was 42.8%〔95%CI (38.4%, 47.1%) 〕, 22.2%〔95%CI (17.8%, 26.7%) 〕and 8.5%〔95%CI (6.3%, 10.6%) 〕, respectively. The prevalence of frailty in elderly patients surveyed in 2001—2010, 2011—2015, and 2016—2020 was 21.0%〔95%CI (13.2%, 28.8%) 〕, 19.0%〔95%CI (13.1%, 24.8%) 〕and 37.7%〔95%CI (22.6%, 52.9%) 〕, respectively. Conclusion The prevalence of frailty in elderly patients with comorbidity is gradually increasing, with differences by number of co-morbidities, continents, assessment tools and study sites. Therefore, relevant personnel should pay attention to early screening of frailty in elderly patients with comorbidity and take timely measures to prevent the development of frailty in elderly patients with comorbidity.

ObjectiveTo analyze the prevalence rate of non-suicidal self-injury （NSSI） behavior in Chinese adolescents with depression， so as to provide references for the intervention of NSSI behavior in adolescents with depression.MethodsThe literature databases such as CNKI， VIP， Wanfang， China Biology Medicine Disc， PubMed， Web of Science， Cochrane Library and Embase were searched via computer for the cross-sectional studies related to the prevalence of NSSI behavior in adolescents with depression published from inception to February， 2020. Then the eligibility assessment， data extraction and assessment of methodological quality were performed independently by two reviewers， and the Meta-analysis was performed by using RevMan 5.4.ResultsA total of 2 238 adolescents in 10 studies were included. Meta-analysis yielded that the prevalence rate of NSSI behavior in Chinese adolescents with depression was 51% （95% CI： 43%~59%）. Subgroup analysis of NSSI behavior in adolescents with depression implied that the prevalence rate was 36% （95% CI： 22%~50%） in female adolescents， which was higher than 18% （95% CI： 12%~24%） in male adolescents. The prevalence rate of NSSI behavior was 57% （95% CI： 38%~77%） in depression adolescents with suicidal ideation， which was higher than 4% （95% CI： 0~8%） in those without suicidal ideation. The prevalence rate of NSSI behavior was 54% （95% CI： 41%~67%） in depression adolescents diagnosed with Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5）， which was higher than 46% （95% CI： 40%~51%） in those diagnosed with the International Classification of Diseases， tenth edition （ICD-10）. The prevalence rate of NSSI behavior was 52% （95% CI： 41%~63%） in depression adolescents in the literatures with quality score of 7， which was close to 50% （95% CI： 44%~55%） in depression adolescents in the literatures with quality score of 6. The comparison of above subgroups all had statistical differences （P

Background: Individuals who perceive medical discrimination often face adverse consequences. How individuals perceive their own aging experiences may influence perceived medical discrimination due to age by generating expectations that they will receive poor treatment from clinicians, which may be amplified for individuals who also perceive discrimination because of race. This study explored the relationship between self‐perceptions of aging (SPA) and perceived medical discrimination due to age, race, and other reasons. Methods: We used three waves (2008, 2012, 2016) from the nationally representative Health and Retirement Study (HRS) data. Our sample included 10,188 community‐residing individuals aged 51 and over. SPA were measured by two domains: positive SPA and negative SPA. Multinomial logistic regression that adjusted for demographic, health characteristics, and year‐fixed effects was conducted to estimate the relationship between SPA and categories of perceived medical discrimination (age, race, age and race, and other). Results: Approximately 11% of the population perceived discrimination because of age or race in the medical setting from 2008 to 2016. Older adults who had a positive SPA were 15% [Adjusted relative risk ratio (ARR): 0.85, 95% CI: 0.79–0.91], 13% [ARRR: 0.87, 95% CI: 0.76–1.00], and 20% [ARRR: 0.80, 95% CI: 0.74–0.88] less likely to experience perceived medical discrimination due to age, race, and the intersection of age and race, respectively, than those who did not, holding other factors constant. Those who held a negative SPA were 38% [ARRR: 1.38, 95% CI: 1.28–1.48] more likely to report perceived medical discrimination due to age and 12% [ARRR: 1.12, 95% CI: 1.03–1.21] more likely to report perceived medical discrimination due to other reasons. Conclusions: Holding a positive perception of aging may help reduce perceived medical discrimination because of age and race, which may in turn improve communication and lead to timely and appropriate treatment. See related Editorial by Timothy W. Farrell. in this issue. [ABSTRACT FROM AUTHOR]

Examination of a recent open-system Ehrenfest dynamics simulation suggests that a vibration-mediate resonance may play a pivotal role in the charge transfer across a donor–acceptor interface in an organic solar cell. Based on this, a concise dissipative two-level electronic system coupled to a molecular vibrational mode is proposed and solved quantum mechanically. It is found that the charge transfer is enhanced substantially when the vibrational energy quanta is equal to the electronic energy loss across the interface. This vibration-mediate resonant charge transfer process is ultrafast, occurring within 100 fs, comparable to experimental findings. The open-system Ehrenfest dynamics simulation of the two-level model is carried out, and similar results are obtained, which confirms further that the earlier open-system Ehrenfest dynamics simulation indeed correctly predicted the occurrence of the resonant charge transfer across the donor–acceptor interface. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the possibility of tyrosine kinase inhibitors (TKIs) discontinuation in chronic myeloid leukemia (CML) patients who obtained sustained deep molecular response (DMR) and to explore the prognostic role of NK cells in treatment-free remission (TFR). Sixty CML patients who discontinued TKI treatment were enrolled, and we also investigated the immune profiles in 27 CML patients after TKI cessation. Of the 60 patients, the estimated TFR rate was 60.8% [95% CI: 49.5–74.8%] at 12 months. Patients who had longer TKI duration, major molecular response, and DMR maintenance time had a significantly higher TFR rate. And a higher percentage of NKG2A+NK cells and NKG2A+CD56brightCD16−NK cells were independent prognostic factors of TFR in multivariate analysis. These results indicate the practicality of the cessation of TKIs and patients with stable NK cell counts accompanied by higher cytotoxicity and increased killing capacity are more inclined to get sustained treatment-free survival. [ABSTRACT FROM AUTHOR]

Artificial shape-morphing hydrogels are emerging toward various applications, spanning from electronic skins to healthcare. However, the low freezing and drying tolerance of hydrogels hinder their practical applications in challenging environments, such as subzero temperatures and arid conditions. Herein, we report on a shape-morphing system of tough organohydrogels enabled by the spatially encoded rigid structures and its applications in conformal packaging of "island–bridge" stretchable electronics. To validate this method, programmable shape morphing of Fe (III) ion-stiffened Ca-alginate/polyacrylamide (PAAm) tough organohydrogels down to −50 °C, with long-term preservation of their 3D shapes at arid or even vacuum conditions, was successfully demonstrated, respectively. To further illustrate the potency of this approach, the as-made organohydrogels were employed as a material for the conformal packaging of non-stretchable rigid electronic components and highly stretchable liquid metal (galinstan) conductors, forming a so-called "island–bridge" stretchable circuit. The conformal packaging well addresses the mechanical mismatch between components with different elastic moduli. As such, the as-made stretchable shape-morphing device exhibits a remarkably high mechanical durability that can withstand strains as high as 1000% and possesses long-term stability required for applications under challenging conditions. [ABSTRACT FROM AUTHOR]

The new generation of the high-efficiency video coding (HEVC) video coding standard has improved compression performance and brought considerable coding complexity. Therefore, reducing the perception redundancy of video to obtain a better compression effect is the new direction of video development at present. In this paper, the HEVC is improved and enhanced from the aspects of a video saliency algorithm based on an attention mechanism and a video compression algorithm based on perception priority. In terms of video saliency, this paper proposes a spatial saliency algorithm based on a convolutional neural network and a temporal saliency algorithm based on motion vector. The saliency algorithm can combine the motion estimation results of each block during the HEVC compression on the basis of convolutional neural network and carry out adaptive dynamic fusion of the two, to complete the saliency map of the input video. In the aspect of the video compression algorithm with perception priority, this paper proposes a more flexible QP selection method, which selects its corresponding QP according to the saliency value of CU. At the same time, we propose a new rate-distortion optimization algorithm, which integrates the current block’s saliency feature into the traditional rate-distortion calculation method, to guide the allocation of bits and achieve the purpose of perception priority. The experimental results proved the superiority of the proposed method over the state-of-the-art perceptual coding algorithms in terms of saliency detection and perceptual compression quality. [ABSTRACT FROM AUTHOR]

The perceptual video coding systems for optimization have been developed on the basis of different attributes of the human visual system. The attention-based coding system is considered as an important part of it. The saliency map method representing the region-of-interest (ROI) from the video signal has become a reliable method due to advances in the computer performance and the visual algorithms. In the present study, we propose a hybrid compression algorithm that uses the deep convolutional neural network to compute the spatial saliency followed by extraction of the temporal saliency from the compressed-domain motion information. The level of uncertainty is calculated to combine to form the video's saliency map. Afterwards, the QP search range is dynamically adjusted in HEVC, and a rate distortion calculation method is proposed to choose the pattern and guide the allocation of bits during the video compression process. Empirical reporting results proved the superiority of the proposed method over the state-of-the-art perceptual coding algorithms in terms of saliency detection and perceptual compression quality. [ABSTRACT FROM AUTHOR]

Flood frequency analysis generally involves the use of simple parametric probability distributions to smooth and extrapolate the information provided by short flood records to estimate extreme flood flow quantiles. Parametric probability distributions can have difficulty simultaneously fitting both the largest and smallest floods. A danger is that the smallest observations in a record can distort the exceedance probabilities assigned to the large floods of interest. The identification and treatment of such Potentially Influential Low Floods (PILFs) frees a fitting algorithm to describe the distribution of the larger observations. This can allow parametric flood frequency analysis to be both efficient, and also robust to deviations from the proposed probability model's lower tail. Historically, PILF identification involved subjective judgement. We propose a new multiple Grubbs-Beck outlier test (MGBT) for objective PILF identification. MGBT PILF identification rates (akin to Type I errors) are reported for the lognormal (LN) distribution and the log-Pearson Type III (LP3) distribution with a variety of skew coefficients. MGBT PILF identification generally matched subjective identification from a recent California flood frequency study. Monte Carlo results show that censoring of PILFs identified by the MGBT algorithm improves the extreme quantile estimator efficiency of the expected moments algorithm (EMA) for negatively skewed LP3 distributions and has little effect for zero or positive skews; simultaneously it protects against deviations from the LP3 in the lower tail, as illustrated by distorted LN examples. Thus, MGBT generally makes flood frequency analysis based on the LP3 distribution with EMA both more accurate and more robust. [ABSTRACT FROM AUTHOR]

Metastasis accounts for the vast majority of cancer deaths. To minimize metastasis-associated mortality, it is crucially important to evaluate the metastatic potential (M.P.), that is, defined as a tendency of a primary tumor to colonize a distant organ. Dysregulated pH in solid tumors, especially the acidification of extracellular pH (pHe) promotes dormant metastasis by driving protease-mediated digestion, disrupting cell-matrix interaction and increasing migration of cancer cells. Therefore, imaging intratumoral acidosis creates a unique opportunity to evaluate the M.P. In this work, a novel pH activatable probe was developed, in which two near-infrared (NIR) fluorophores were conjugated via a flexible and acid liable linkage. While the fluorescence of this probe is quenched due to intramolecular dimeric aggregate under neutral environment, the cleavage of pH liable linkage with the concomitant disruption of aggregates in acidic tumor microenvironment results in a remarkable fluorescence enhancement. This probe not only visualized the primary tumors with high target to background (T/B) signal ratio in vivo, but also revealed the correlation between the M.P. and acidosis distribution pattern in tumor. While the acidosis locate dispersedly at tumor periphery in highly metastatic tumor, it distribute more widely in lowly metastatic tumor and the acidification degree increases substantially from the margin to core areas. This pH activatable NIR fluorescent probe holds the potential to evaluate the M.P., monitor the therapeutic response and predict the prognosis by delineating acidosis in tumors. [ABSTRACT FROM AUTHOR]

Large scale production of water-intensive industrial products can intensify water scarcity, resulting in potential unsustainable water use at local and regional scales. This study proposes a methodological framework for assessing the WF sustainability of multiple interdependent products in a system, and one of China's four major large modern coal chemical industry bases is used as a case study. A Mixed-Unit Input-Output (MUIO) model was applied to calculate the blue water footprint (WF) for 19 major coal-based energy and chemicals in the study area, based on which the WF sustainability of production of the products were assessed using different indicators. Technical coefficient matrix and direct water consumption vector of the products were constructed based a database that were built by field research in the study area. Accounting result indicates that the blue WF of the coal-based products range from 2.5 × 10−4 m3/kWh for coal-fired power to 55.25 m3/t for Polytetrahydrofuran. The sustainability assessment reveals that the blue WF of all products produced in the study area are sustainable at both product and regional levels, while over half of them have reached the advanced level. However, the blue WF of a few products with large production capacities has just crossed the sustainable thresholds, posing potential threat to the local environment. This paper concludes with a discussion on the choice of blue WF accounting approach, methods to promote WF sustainability of coal-based products, and suggestions for the WF management in general. [ABSTRACT FROM AUTHOR]

The water scarcity in China's coal bases is intensifying due to rapid development of modern coal chemical industry and inefficient water utilization. Previous studies on industrial water optimization were predominantly focused on direct water, overlooking the associated indirect water consumptions throughout supply chains. In this study, a water footprint (WF)-based allocation optimization framework is developed to obtain optimal solutions for water resources utilization constrained by quantity of water supply and coal chemical production related limiting factors. The framework comprises a novel WF accounting model especially used for the coal-to-chemical industry and a water allocation optimization model that integrates direct and indirect water consumptions. A typical major large-scale coal base in China was chosen as the study area. Results showed that the cradle-to-gate WF of the various coal-based products ranged from 2.01 m3/t to 70.85 m3/t, in which the internal operational and supply-chain blue WFs were the dominant contributors. Statistical analysis suggested that the volumetric WF of the coal-based products was strongly correlated with both market price and production stage while the variation of WF increased as products were further processed. Optimization result indicated that the maximized economic income of the products under current scenario was 66.23 billion CNY/year in the study area, whereas the overlapping of limited water resources and the insufficiency of downstream production capacity restricted the economic performance by over 20%. In addition, sensitivity analysis was conducted and the results showed that, in order to improve the overall economic income, deployment of more advanced technologies for saving water should be prioritized over that for saving feedstock, while conservation of power was the least preferable. Unlabelled Image • A water footprint (WF)-based allocation optimization framework is developed. • A novel WF method is proposed to assess WF of various coal-to-chemicals. • The total WF of coal-to-chemicals ranges from 2.01 m3/t to 70.85 m3/t. • The maximized local income rises 20% with adequate water and methanol supplies. [ABSTRACT FROM AUTHOR]

The existence of water markets establishes water prices, promoting trading of water from low- to high-valued uses. However, market participants can face uncertainty when asking and offering prices because water rights are heterogeneous, resulting in inefficiency of the market. This paper proposes three random forest regression models (RFR) to predict water price in the western United States: a full variable set model and two reduced ones with optimal numbers of variables using a backward variable elimination (BVE) approach. Transactions of 12 semiarid states, from 1987 to 2009, and a dataset containing various predictors, were assembled. Multiple replications of k-fold cross-validation were applied to assess the model performance and their generalizability was tested on unused data. The importance of price influencing factors was then analyzed based on two plausible variable importance rankings. Results show that the RFR models have good predictive power for water price. They outperform a baseline model without leading to overfitting. Also, the higher degree of accuracy of the reduced models is insignificant, reflecting the robustness of RFR to including lower informative variables. This study suggests that, due to its ability to automatically learn from and make predictions on data, RFR-based models can aid water market participants in making more efficient decisions. [ABSTRACT FROM AUTHOR]