Clinical applications of radiomics in non-small cell lung cancer patients with immune checkpoint inhibitor-related pneumonitis

Immune checkpoint inhibitors (ICIs) modulate the body’s immune function to treat tumors but may also induce pneumonitis. Immune checkpoint inhibitor-related pneumonitis (ICIP) is a serious immune-related adverse event (irAE). Immunotherapy is currently approved as a first-line treatment for non-small cell lung cancer (NSCLC), and the incidence of ICIP in NSCLC patients can be as high as 5%-19% in clinical practice. ICIP can be severe enough to lead to the death of NSCLC patients, but there is a lack of a gold standard for the diagnosis of ICIP. Radiomics is a method that uses computational techniques to analyze medical images (e.g., CT, MRI, PET) and extract important features from them, which can be used to solve classification and regression problems in the clinic. Radiomics has been applied to predict and identify ICIP in NSCLC patients in the hope of transforming clinical qualitative problems into quantitative ones, thus improving the diagnosis and treatment of ICIP. In this review, we summarize the pathogenesis of ICIP and the process of radiomics feature extraction, review the clinical application of radiomics in ICIP of NSCLC patients, and discuss its future application prospects

Radio emission of tidal disruption events from wind-cloud interaction

Winds can be launched in tidal disruption event (TDE). It has been proposed that the winds can interact with the cloud surrounding the black hole, produce bow shocks, accelerate electrons, and produce radio emission. We restudy the wind-cloud interaction model. We employ the properties of winds found by the radiation hydrodynamic simulations of super-Eddington circularized accretion flow in TDEs. We can calculate the peak radio emission frequency, the luminosity at the peak frequency, and their time-evolution based on the TDEs wind-cloud interaction model. We find that the model predicted peak radio emission frequency, the luminosity at peak frequency, and their time evolution can be well consistent with those in TDEs AT2019dsg and ASASSN-14li. This indicates that in these two radio TDEs, the wind-cloud interaction mechanism may be responsible for the radio emission.Comment: 11 pages, 10 figures, accepted to MNRA

Generation of multi-site stochastic daily rainfall with four weather generators:a case study of Gloucester catchment in Australia

Four weather generators, namely, R-package version of the Generalised Linear Model for daily Climate time series (RGLIMCLIM), Stochastic Climate Library (SCL), R-package multi-site precipitation generator (RGENERATRPREC) and R-package Multi-site Auto-regressive Weather GENerator (RMAWGEN), were used to generate multi-sites stochastic daily rainfall for a small catchment in Australia. The results show the following: (1) All four models produced reasonable results in terms of annual, monthly and daily rainfall occurrence and amount, as well as daily extreme, multi-day extremes and dry/wet spell length. However, they also simulated a large range of variability, which not only demonstrates the advantages of multiple weather generators rather than a single model but also is more suitable for climate change and variability impact studies. (2) Every model has its own advantages and disadvantages due to their different theories and principles. This enhances the benefits of using multiple models. (3) The models can be further calibrated/improved to have a “better” performance in comparison with observations. However, it was chosen not to do so in this case study for two reasons: to obtain a full range of climate variability and to acknowledge the uncertainties associated with observation data. The latter are interpolated from limited stations and therefore have high pairwise correlations—ranging from 0.69 to 0.99 with a median and mean value of 0.87 and 0.88, respectively, for daily rainfall. These conclusions were drawn from a case study in Australia, but could be extended to general guidelines of using weather generators for climate change and variability studies

Attributing variations of temporal and spatial groundwater recharge: a statistical analysis of climatic and non-climatic factors

This paper demonstrated the benefits of statistical methods when investigating the climatic and non-climatic drivers responsible for variations in groundwater recharge with a series of up to 43 years of annual recharge for 426 bores in South-East South Australia. We identified the factors influencing groundwater recharge based on 71 climatic metrics and 13 non-climatic metrics (including groundwater abstraction). The results showed: 1) Rainfall during April to October was the most important variable influencing recharge temporal variation, with its decline identified as the most significant factor related to recharge reduction; 2) In contrast, a negative correlation between rainfall during December to February (DJF) and annual groundwater recharge was found. This suggests that a seasonal shift in rainfall (such as decreasing rainfall during April to October and an increase during DJF) can result in a decline in recharge even when the annual rainfall remains unchanged; 3) The length of wet spells (consecutive rain days) and increasing PET were additional significant predictors for recharge temporal variation. It demonstrated that a simple empirical relationship (such as recharge as a fixed percentage of rainfall) is not a reliable estimation of renewable groundwater resources under changing climatic conditions; 4) There is a statistically significant spatial correlation between mean groundwater depth and recharge, and this implies that a reduction in rainfall can lead to a positive feedback loop of declining recharge and water level; 5) Spatially the most statistically significant factors influencing groundwater recharge were soil types and land attributes. The findings of this study can identify which stressors should be included when investigating the impact of climate change on groundwater recharge

Uncertainties of statistical downscaling from predictor selection: Equifinality and transferability

The nonhomogeneous hidden Markov model (NHMM) statistical downscaling model, 38 catchments in southeast Australia and 19 general circulation models (GCMs) were used in this study to demonstrate statistical downscaling uncertainties caused by equifinality to and transferability. That is to say, there could be multiple sets of predictors that give similar daily rainfall simulation results for both calibration and validation periods, but project different amounts (or even directions of change) of rainfall changing in the future. Results indicated that two sets of predictors (Set 1 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and specific humidity at 700 hPa and Set 2 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and dewpoint temperature depression at 850 hPa) as inputs to the NHMM produced satisfactory results of seasonal rainfall in comparison with observations. For example, during the model calibration period, the relative errors across the 38 catchments ranged from 0.48 to 1.76% with a mean value of 1.09% for the predictor Set 1, and from 0.22 to 2.24% with a mean value of 1.16% for the predictor Set 2. However, the changes of future rainfall from NHMM projections based on 19 GCMs produced projections with a different sign for these two different sets of predictors: Set 1 predictors project an increase of future rainfall with magnitudes depending on future time periods and emission scenarios, but Set 2 predictors project a decline of future rainfall. Such divergent projections may present a significant challenge for applications of statistical downscaling as well as climate change impact studies, and could potentially imply caveats in many existing studies in the literature

Trends of major hydroclimatic variables in the Tarim River basin during the past 50 years

The nonparametric Mann-Kendall test was used to detect the trends of major hydroclimatic variables in the Tarim River Basin, the largest inland river basin in China for the period of 1960-2007. Results showed that both mean annual air temperature and precipitation experienced an increasing trend, while annual streamflow demonstrated a mixed trend of decreasing and increasing: The mountainous region upstream showed an increasing trend and the region downstream exhibited a decreasing trend. impacts of the increased air temperature on streamflow have shown different characteristics depending on location and seasons: it has positive effect on the runoff at mountainous region due to snowmelt and glacier-melt in spring, but negative effect on the runoff at plain area due to the increase of actual evaporation in summer. in addition, human activity contributed to the declining of streamflow in the arid plain oases at downstream of the Tarim River Basin. The results obtained in this paper can be used as a reference for the planning and management of water resources to maintain the health of the river system. (C) 2009 Elsevier Ltd. All rights reserved

Wielding the sword: President Xi’s new anti-corruption campaign

A state achieves legitimacy through multiple sources, one of which is the effectiveness of its governance. Generations of scholars since Hobbes have identified the maintenance of peace and order as core functions of a legitimate state. In the modern world, economic prosperity, social stability and effective control of corruption often provide adequate compensation for a deficit of democracy. Corruption closely correlates with legitimacy. While a perceived pervasive, endemic corruption undermines the legitimacy of a regime, a successful anti-corruption campaign can allow a regime to recover from a crisis of legitimacy (Gilley 2009; Seligson and Booth 2009). This is the rationale behind the periodical campaigns against corruption that have been conducted by the Chinese Communist Party (‘Party’ or ‘CCP’) (Manion 2004; Wedeman 2012). Political leaders in China have found it expedient to use anti-corruption campaigns to remove their political foes, to rein in the bureaucracy and to restore public confidence in their ability to rule. Through anti-corruption campaigns, emerging political leaders consolidate their political power, secure loyalty from political factions and regional political forces, and enhance their legitimacy in the eyes of the general public. In an authoritarian state that experiences a high level of corruption, an anti-corruption campaign is a delicate political battle that addresses two significant concerns. The first concern is to orchestrate the campaign so that it is regime-reinforcing instead of regime-undermining. To remain credible, the regime must demonstrate its willingness and capacity to punish corrupt officials at the highest levels.preprin