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Aims Design Methods Results Conclusion Impact Statement Patient or Public Contribution To analyse the current status of psychological resilience in Parkinson's disease (PD) patients and its correlation with social support and coping style.A cross‐sectional study.PD patients hospitalized in a tertiary‐level hospital in Shijiazhuang, Hebei Province, from March 2022 to March 2023 were selected for the study using the convenience sampling method. A general information questionnaire, psychological resilience scale, Medical Coping Modes Questionnaire and Perceived Social Support Scale were used to investigate 111 cases of PD. SPSS 25.0 software was used for statistical analysis. The data were analysed using independent samples t‐test, one‐way ANOVA, multiple linear regression analysis and the Pearson correlation coefficient.Parkinson's disease patients have a moderate level of psychological resilience. The results of the Pearson correlation analyses showed that the level of psychological resilience was positively correlated with social support and confrontation and was negatively correlated with avoidance and acceptance‐resignation. The results of multiple linear regression analysis showed that social support and acceptance‐resignation were the influencing factors of psychological resilience in PD patients.The psychological resilience of PD patients is at a moderate level. Social support and acceptance‐resignation are the factors influencing the psychological resilience of PD patients.This study analysed the level of psychological resilience in PD patients and its correlation with social support and coping style from the perspective of positive psychology to provide some reference for targeted clinical interventions. Our study found that social support and acceptance‐resignation are influential factors in psychological resilience in PD patients. Medical staff should encourage patients to face the disease positively and their social support should be increased in order to improve their level of psychological resilience.No patient or public contribution. [ABSTRACT FROM AUTHOR]

Dietary methionine restriction (MR) is associated with a spectrum of health‐promoting benefits. Being conducive to prevention of chronic diseases and extension of life span, MR can activate integrated responses at metabolic, transcriptional, and physiological levels. However, how the mitochondria of MR influence metabolic phenotypes remains elusive. Here, we provide a summary of cellular functions of methionine metabolism and an overview of the current understanding of effector mechanisms of MR, with a focus on the aspect of mitochondria‐mediated responses. We propose that mitochondria can sense and respond to MR through a modulatory role of lipoylation, a mitochondrial protein modification sensitized by MR. [ABSTRACT FROM AUTHOR]

This work develops a new robust multi‐objective model predictive control (MoMPC) strategy for constrained non‐linear systems with bounded disturbances. The multiple objectives are always contradictory, and the presence of disturbances may result in the violation of state constraints and instability of the controlled system. Firstly, the conflict between multiple objectives is reconciled by minimizing the distance of the cost function vector to the vector of independently minimised objectives obtained by solving a set of steady‐state optimisation problems. Then the contractive state set, which takes into account the effect of disturbances on system states, is constructed to guarantee the robust satisfaction of state constraints. Finally, a stability constraint updated online by solving an auxiliary optimization problem is established to ensure the robust stability of the system under MoMPC. An isothermal chemical reactor system is employed to verify the effectiveness of the controller proposed here. [ABSTRACT FROM AUTHOR]

To assess the abilities of global climate models (GCMs) on simulating the spatiotemporal distribution of marine heatwaves (MHWs), GCMs from the Coupled Model Intercomparison Program in Phase 6 (CMIP6) were evaluated from a historical period between 1985 and 2014 in the Northwest Pacific Ocean using a dataset that synthesizes remote sensing data. MHW simulation capabilities were assessed using Rank Score (RS) and Comprehensive Rating (MR) metrics that include both spatial and temporal scoring metrics. It was found that most CMIP6 models overestimate cumulative intensity, while mean and maximum intensities, in addition to the duration, were underestimated in the historical period. Possible future changes in MHWs were also examined based on the rank-based weighting ensembles under four shared socioeconomic pathways (SSPs) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). MHWs were identified using both a fixed 30-year baseline and a 30-year sliding baseline. In all scenarios, all MHWs metrics except frequency will have an increasing trend for the fixed baseline method. The frequency of MHWs will decrease after the 2050s. Days will first increase and then stabilize under various scenarios. MHWs will take place for more than 300 days by the end of the 21st century for the SSP5-8.5 scenario. The cumulative intensity in the SSP5-8.5 scenario is roughly six times higher than that in the SSP1-2.6 scenario by the end of the 21st century. A fixed baseline will result in near-permanent MHWs at the end of the 21st century. There will be no permanent MHWs at the end of the 21st century. Using the 30-year shifting baseline to define the MHWs can improve future MHW projections by capturing the spatiotemporal variability features of the MHWs. [ABSTRACT FROM AUTHOR]

Accurate estimation of root-zone soil moisture (SM) is of great significance for accurate irrigation management. This study was purposed to identify planted-by-planted mapping of root-zone SM on three critical fruit growth periods based on UAV multispectral images using three machine learning (ML) algorithms in a kiwifruit orchard in Shaanxi, China. Several spectral variables were selected based on variable importance (VIP) rankings, including reflectance Ri at wavelengths 560, 668, 740, and 842 nm. Results indicated that the VIP method effectively reduced 42 vegetation indexes (VIs) to less than 7 with an evaluation accuracy of root-zone SM models. Compared with deep root-zone SM models (SM40 and SM60), shallow root-zone SM models (SM10, SM20, and SM30) have better performance (R2 from 0.65 to 0.82, RRMSE from 0.02 to 0.03, MAE from 0.20 to 0.54) in the three fruit growth stages. Among three ML algorithms, random forest models were recommended for simulating kiwi root-zone SM during the critical fruit growth period. Overall, the proposed planted-by-planted root-zone SM estimation approach can be considered a great tool to upgrade the toolbox of the growers in site-specific field management for the high spatiotemporal resolution of SM maps. [ABSTRACT FROM AUTHOR]

Haze is the phenomenon of visibility degradation caused by extinction effects related to the physicochemical properties of atmospheric particulate matter (APM). Atmosphere heterogeneous reactions can alter the physicochemical properties of APM. Therefore, it is important to understand the atmospheric heterogeneous reactions of APM in order to reveal the cause of haze. Herein, the current situation, developmental trend, source, and composition of APM pollution in China are reviewed. Additionally, we introduce the reaction characteristics and key chemical processes of common inorganic, organic, and mixed pollutant gases on the surface of mineral particles. The effects of mineral particulate matter on aggregation, regulation, and catalysis in the formation of atmospheric aerosols and the synergistic reaction mechanism of SO2, NO2, O3, and VOCs on the surfaces of different mineral particles are summarized. The problems existing in the current research on heterogeneous reactions on the surfaces of mineral particles are also evaluated. This paper aims to gain a deep understanding of the mechanism of mineral particulate matter promoting the formation of secondary aerosols and attempts to provide theoretical support for effective haze control. [ABSTRACT FROM AUTHOR]

Ground water inflow from an overlying aquifer happens frequently in underground engineering; for properly controlling ground water during construction, the most important tasks are to assess the possibility and the probable water inflow, which depends on the ground water recharge characteristics. However, less work has been carried out on this topic. In order to study the water inflow variation characteristics including dynamic replenishment and static reserve release from a submersible aquifer, sand-tank seepage experiments on a dewatering well seepage from an aquifer bottom under the conditions of different water pressure heads insides the dewatering well (P) were designed and performed. The results show that (1) when the dewatering beginning, the water inflow increases to a peak value rapidly and then decreases following a first-order exponential decay function. In the initial phase, the water inflow is mainly composed of static reserve release, which decreases quickly with time also following a first-order exponential decay function. Meanwhile, the recharge of dynamic replenishment quickly increases with time following a first-order exponential growth function, which mainly forms the water inflow in the quasi-steady state. (2) The equal time of dynamic and static reserve release and the quasi-steady state time both present a first-order exponential decay function with the decrease of P. (3) The peak water inflow should perform at the beginning of dewatering which presents a little late after the beginning of dewatering and increases with the decreasing of P following a linear function. The results will play important references for water inflow prediction and calculation from overlying aquifers for underground projects. [ABSTRACT FROM AUTHOR]

The temporal and spatial distributions of regional irrigation water productivity (RIWP) are crucial for making decisions related to agriculture, especially in arid irrigated areas with complex cropping patterns. Thus, in this study, we developed a new RIWP model for an irrigated agricultural area with complex cropping patterns. The model couples the irrigation- and drainage-driven soil water and salinity dynamics and shallow groundwater movement in order to quantify the temporal and spatial distributions of the target hydrological and biophysical variables. We divided the study area into 1 km × 1 km hydrological response units (HRUs). In each HRU, we considered four land use types: sunflower fields, wheat fields, maize fields, and uncultivated lands (bare soil). We coupled the regional soil hydrological processes and groundwater flow by taking a weighted average of the water exchange between unsaturated soil and groundwater under different land use types. The RIWP model was calibrated and validated using 8 years of hydrological variables obtained from regional observation sites in a typical arid irrigation area in North China, the Hetao Irrigation District. The model simulated soil moisture and salinity reasonably well as well as groundwater table depths and salinity. However, overestimations of groundwater discharge were detected in both the calibration and validation due to the assumption of well-operated drainage ditch conditions; regional evapotranspiration (ET) was reasonably estimated, whereas ET in the uncultivated area was slightly underestimated in the RIWP model. A sensitivity analysis indicated that the soil evaporation coefficient and the specific yield were the key parameters for the RIWP simulation. The results showed that the RIWP decreased from maize to sunflower to wheat from 2006 to 2013. It was also found that the maximum RIWP was reached when the groundwater table depth was between 2 and 4 m, regardless of the irrigation water depth applied. This implies the importance of groundwater table control on the RIWP. Overall, our distributed RIWP model can effectively simulate the temporal and spatial distribution of the RIWP and provide critical water allocation suggestions for decision-makers. [ABSTRACT FROM AUTHOR]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Crop models are widely used to assist in agricultural management decision-making and water productivity optimization. However, traditional crop models often depend on artificial and specific field management inputs, posing challenges in maintaining crops within a desired stress range. Consequently, the derived optimization schemes from these models become highly uncertain. Moreover, the complexity of the mechanisms involved and the multitude of parameters make it challenging to apply traditional crop models uniformly across various crops and regions. In this study, we have developed a novel crop model called WHCrop (Water-Heat Driven Crop model) that effectively captures, reflects, and controls the impact of various environmental factors (meteorology, topography, soil, and management) on crop growth process. The WHCrop model combines the simulation principles of biomass and yield from the CERES module in the DSSAT model, along with the soil water balance from the AquaCrop model, to estimate the dynamics of crop growth and production processes. Results indicated that WHCrop-based simulations, including canopy cover (CC), daily evapotranspiration (ET), and yield, matched well with ground-based measurements, and were better than the traditional crop model (DSSAT and AquaCrop) at both field and regional scales, especially under deficient irrigation conditions. Besides capturing the key variables associated with crop growth, WHCrop model could reproduce the adaptive response of these various to regional-scale temperature changes. Notably, the WHCrop model could effectively minimize uncertainties resulting from individual environmental change, thanks its incorporation of dynamic response mechanisms for crop growth under stress factors. Overall, the novel and informative WHCrop model offers some advantages over traditional crop models since it allows for optimal decision making to be derived from the randomly different inputs. As a result, the WHCrop model proves instrumental in assisting decision-makers in formulating critical water allocation strategies and developing effective management recommendations to enhance regional agricultural water productivity. • WHCrop model simulates crop growth dynamics using water and heat drive. • WHCrop model enables randomly varied inputs for optimal decision-making. • WHCrop model simulates daily crop growth responses to water stress and climate changes. • WHCrop model needs fewer and readily available input data than traditional crop model. • WHCrop outperformed traditional crop models in simulating crop growth across scales. [ABSTRACT FROM AUTHOR]

Improving the efficiency of water consumption and water productivity is the key approach to satisfy sustainable water resource supply and food demand. As effective measures, water saving practices are implemented in arid and semi-arid regions. For areas with shallow groundwater, water used for irrigation is not entirely consumptively used. The majority of irrigation water infiltrations below the root zone are stored in shallow groundwater. This can be reused as groundwater based evapotranspiration (ET g ) at the regional scale. Thus, actual regional efficiency of water consumption (REWC) based on all water within the hydrological system is greater than based on consumptive use only. Accurately evaluating the response of REWC and regional water productivity (RWP) to water saving practices is essential due to the complexity of the hydrological system. In this study, regional ET g and regional evapotranspiration (ET) of the past 20 years were reproduced in a typical arid irrigation district with shallow groundwater based on the water balance method. Furthermore, REWC and RWP were estimated to investigate the impact of water saving practices to regional water use. Simulation results show that groundwater is a significant water source of regional ET in arid regions with a shallow aquifer and contributes more than 16% of regional ET for the irrigation district. Water saving practice implementation enhances the contribution of groundwater to ET. After water saving practices implementation, annual REWC and RWP have been improved by 0.07 and 0.1 kg/m 3 , respectively. Furthermore, negative correlation between REWC and I + P (the total water supply including rainfall and irrigation water diversion) and positive correlation between RWP and REWC demonstrate that water saving practices can reduce the non-beneficial water losses by evaporation and enhance productivity by a lower groundwater table. Overall, shallow groundwater plays an important role to enhance REWC and RWP and the contribution of groundwater to regional water use needs to be considered as part of a reasonable water saving strategy towards a sustainable agricultural system. [ABSTRACT FROM AUTHOR]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quantitative evaluation of best management practice (BMP) effectiveness can help stakeholders to make better watershed management decisions. However, such evaluations are always challenging as they require complex algorithms to simulate the relevant hydrological processes, crop growth and the corresponding pollutant transport pathways in order to evaluate potential BMPs and select the best one for the specific field conditions. In this study, a web-based interface (CalBMP) was developed to predict BMP effectiveness in California, focusing on pesticide modeling at the field scale. With built-in databases for soil, weather, crop, pesticides, and BMPs, users can run simulations for baseline and BMP scenarios using their site-specific field conditions by simply providing the field information, such as zip code, soil, crop management, and pesticide application data. CalBMP uses PRZM5 + , a USEPA model, to simulate pesticide transport and fate at the field edge. The CalBMP simulations were validated based on measurements from an alfalfa field study. The results indicated that the CalBMP interface could reasonably simulate the runoff and adsorbed pesticide loss leaving the field with default parameters from previously known field parameters or public databases. CalBMP underestimated sediment erosion, possibly due to uncertainties in field measurements or inaccurate simulation of the temporal distribution of flood irrigation. CalBMP is likely to underestimate pesticides with greater solubility, such as diuron, because PRZM5 + uses the simplified instantaneous equilibrium sorption model. In addition, a strawberry field study was adopted to demonstrate the capability of the CalBMP interface for simulating BMP effectiveness (pesticide reduction percentage in the main pathways) with easy-to-understand graphs and tables. The results indicated that users can easily compare and review the results from multiple scenarios, which could facilitate the decision-making process for mitigating the amount of active ingredient bifenthrin leaving the field. The CalBMP tool provides useful information on pesticide runoff potential and BMP selection at the field scale. With increasingly stringent regulations for water quality protection, CalBMP will add to the growers' toolbox for minimizing the environmental impacts from their inevitable pesticide usage. [Display omitted] • An online best management practice (BMP) modeling tool was developed and validated. • It could help stakeholders identify water quality risks from pesticide use. • It is open access and greatly aid in BMP selection to reduce pesticide runoff. [ABSTRACT FROM AUTHOR]

California's weather is characterized by extreme droughts and floods. This has resulted in overdraft of groundwater aquifers as growers turn to this source of water for irrigation during droughts. California produces 99% of all walnuts in the US, walnut growers are under extreme pressure to optimize crop water use. Water use estimates at the field scale are crucial for growers to refine irrigation scheduling decisions. In this study, two single source remote sensing-based energy balance models (pySEBAL [python-based Surface Energy Balance Algorithm for Land] and SEBS [Surface Energy Balance System algorithm]) for estimating evapotranspiration (ET a) were evaluated against in-situ ET a measurements from surface renewal in two young walnut orchards in California's Sacramento Valley. Strong correlations were obtained between the RS-based estimates and in-situ measurements for both pySEBAL and SEBS from 2017 to 2020, with R2 above 0.87, RMSE ranging from 0.79 to 1.05 mm, and NSE ranging from 0.79 to 0.88. SEBS out-performed pySEBAL on estimating time-series daily ET a for walnut at the field scale. During the mid-season characterized by high wind speed and high temperatures, pySEBAL and SEBS both underestimated ET a while the two models slightly overestimated ET a during the early growing season and post-harvest period. These results indicate the need for future research to focus on improving the performance of pySEBAL and SEBS when simulating time-series ET a under advection and sparse vegetation conditions, to provide more accurate ET a for both in-season and off-season irrigation water management. Comparisons of historical K c and RS-based K c were evaluated, and RS-based K c matched better with the actual water use requirements of developing 2nd to 4th leaf young walnuts orchards. We observed substantial spatiotemporal variability of RS-based K c in wo young walnut orchards at the CAPEX and Kauffman sites. For instance, K c values for the north and south halves of the CAPEX orchard were above 1.2 and 0.9–1.1 respectively. K c values for the north and south halves at the Kauffman site were in a range of 0.6–0.71 and 0.82–0.94 respectively. In other words, conventional irrigation management based on multiplying historical K c and reference evapotranspiration is inadequate for site-specific walnut irrigation management due to spatial and temporal variability in K c. ET a and K c mapping from two single source models were similar in the spatial patterns and provided an overall visual characterization of the spatial variability in crop water use. Overall, RS-based ET a models using freely accessible satellite images and open-source algorithms could be used as an alternative to expensive in-situ measurements for enhancing site-specific young walnut irrigation management. • RS-based ET a estimates for young walnut were compared to in-situ ET a measurements. • SEBS and pySEBAL both got reasonable ET a estimates, and SEBS performed better. • RS-based K c and ET a for developing young walnut captured its spatiotemporal variation. • RS-based ET a models with low cost could be a promising tool in the smart agriculture. • Upgraded irrigation system is necessary to provide enough control to irrigate based on RS-based ET a estimates. [ABSTRACT FROM AUTHOR]

Climate variability and changing cropping patterns are two main factors directly influencing catchment hydrological processes and agricultural productivity. Assessing the response of hydrological processes and agricultural production to the combined impacts is of great importance for enhancing water resources management, water productivity and agriculture sustainability. SWAT (Soil and Water Assessment Tools) models embedded with 2007 and 2018 land use were built for the San Joaquin watershed (SJWS) in California's Central Valley. Global sensitivity analysis were conducted to select parameters that have the largest influence on evapotranspiration (ET) processes. The model was calibrated and validated produced good agreement for monthly ET from remote sensing and yield of 8 major crops using county level reported yields during the periods of 2001–2009 and 2010–2018. Based on the outputs of the calibrated SJWS SWAT model, regional ET showed a significant increase, which was caused by rises in temperature and changing cropping patterns associated with increase in area under nut crop production. Seven major crop yields increased excluding alfalfa, implying that the impacts of increasing temperature and small decreases in precipitation were not dominant factors in explaining observed changes in yield. From periods 2001–2009–2010–2018, total water productivity (WP) increased slightly from 2.11 to 2.15 kg/m3, associated with more water-intensive permanent crop production systems. Total economic water productivity (EWP) increased significantly by 111% from 0.55 to 1.16 US$/m3, which also indicated the substantial economic benefit brought to the SJWS by expanding the land area under high-EWP crops such as nut crops and vegetables. Nutritional water productivity (NWP) for energy, protein and fat were reduced from 1211 kcal/m3, 183 g/m3 and 105 g/m3 to 1141 kcal/m3, 111 g/m3 and 88 g/m3 during the period 2010–2018 mostly due to high water use. Total NWP for calcium was increased from 114 to 145 mg/m3, respectively. This study provides initial insights into the response of WP, EWP and NWP to the changing cropping patterns and climate variability for major crops in the SJWS, which could be used by a wide range of stakeholders including farmers, commodity boards, irrigation districts, groundwater sustainability basins, environmental justice groups and policy makers to optimize water resources planning and management. We recommend creating a comprehensive index that incorporates WP, EWP and NWP for making sustainable water resources planning and management decisions. • Climate variability and cropping patterns change were analyzed from 1999 to 2018. • Regional evapotranspiration significantly increased over the past twenty years. • Total WP only increased slightly for the low WP of nut trees and its extended area. • Total EWP increased significantly by 111% from 0.55 to 1.16 US$/m3. • The paper also explores changes in NWP for various crops grown in the watershed. [ABSTRACT FROM AUTHOR]

Membrane microdomains are nano-scale domains (10–200 nm) enriched in sterols and sphingolipids. They have many important biological functions, including vesicle transport, endocytosis, and pathogen invasion. A previous study reported that the membrane microdomain-associated protein Flotillin1 (Flot1) was involved in plant development in Arabidopsis thaliana; however, whether sterols affect the plant immunity conveyed by Flot1 is unknown. Here, we showed that the root length in sterol-deficient cyclopropylsterol isomerase 1 (cpi1-1) mutants expressing Flot1 was significantly shorter than in control seedlings. The cotyledon epidermal cells in cpi1-1 mutants expressing Flot1 were smaller than in controls. Moreover, variable-angle total internal reflection fluorescence microscopy (VA-TIRFM) and single-particle tracking (SPT) analysis demonstrated that the long-distance Flot1-GFP movement was decreased significantly in cpi1-1 mutants compared with the control seedlings. Meanwhile, the value of the diffusion coefficient Ĝ was dramatically decreased in cpi1-1 mutants after flagelin22 (flg22) treatment compared with the control seedlings, indicating that sterols affect the lateral mobility of Flot1-GFP within the plasma membrane. Importantly, using confocal microscopy, we determined that the endocytosis of Flot1-GFP was decreased in cpi1-1 mutants, which was confirmed by fluorescence cross spectroscopy (FCS) analysis. Hence, these results demonstrate that sterol composition plays a critical role in the plant defense responses of Flot1. [ABSTRACT FROM AUTHOR]

Irrigation is a prerequisite for the sustainable development of agricultural production. With the existing of water resources shortage and climate change, it is of great importance to explore the variation of crop irrigation water requirement (IWR) in the Yellow River Basin (YRB). Based on 1974–2017 meteorological dataset from 96 stations, we analyzed the spatio-temporal variation characteristics of meteorological factors and crop IWR during the growing seasons of four main crops including spring wheat, winter wheat, spring maize and summer maize, respectively. Furthermore, we explored the dominant meteorological factors of the crop IWR variation. The results indicated that daily mean temperature (T) had a significant upward trend, while the effective precipitation (P eff) did not change significantly during the growing season of each crop in the past 44 years. Crop IWR had increasing trend with 9.9 mm/decade, 4.3 mm/decade, 6.4 mm/decade for spring wheat, winter wheat, spring maize respectively, while a slight decreasing trend with − 1.7 mm/decade for summer maize. It is noted that extremely significant increase in crop IWR were mostly located in Ningxia, southern Gansu and eastern Qinghai. Moreover, P eff , net radiation (R n) and relative humidity (RH) were identified as the dominant meteorological factors influencing variations of IWR for all crops. In the context of significant increase in T and uncertain future precipitation patterns, IWR for spring wheat, winter wheat and spring maize in the YRB has shown an upward trend which is not favorable to the sustainable development of water resources. It is urgent to take effective water-saving measures to hedge the adverse impact of climate change on agriculture. These findings can provide scientific basis for rational allocation of agricultural water resources in the YRB. • Irrigation water requirements of main crops in the Yellow River Basin were quantitatively evaluated. • The spatio-temporal variation of meteorological factors during the crop growing seasons was investigated. • The spatial distribution and changing trend of crop irrigation water requirements were characterized. • The dominant meteorological factors of crop irrigation water requirements variation were found out. • It is urgent to take effective water-saving measures to hedge the adverse impact of climate change on agriculture. [ABSTRACT FROM AUTHOR]

We describe a protocol for measuring phospholipid class and fatty acid composition in the budding yeast Saccharomyces cerevisiae using a liquid chromatography-mass spectrometry (LC-MS)-based approach. We compile a mass spectral-retention time library verified for major phospholipids in the budding yeast and showcase the profiling process of phospholipid compositions in mutants with defective syntheses of phosphatidylethanolamine (PE) and phosphatidylcholine (PC). We further provide methods for extracting and quantifying phospholipids in mammalian systems. For complete details on the use and execution of this protocol, please refer to Fang et al. (2022)., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Brain metastasis is common in patients with lung cancer and has a negative impact on overall survival (OS). The aim of this study was to investigate therapeutic effects and prognosis-related factors for survival of patients with pulmonary adenocarcinoma and brain metastasis., Methods: This was a retrospective study involving the data of patients with pulmonary adenocarcinoma and brain metastasis who were treated at the Department of Oncology, Tianjin Medical University General Hospital. Participants were divided into 2 groups: the initial-metastasis group (brain metastases at first visit), and the late-metastasis group (developed metastasis during treatment). The quantitative index was described as mean ± standard deviation (SD), independent sample t-test was used to calculate the P value. All data were processed using the software SPSS 20.0 software package., Results: There were a total of 43 patients in the initial-metastasis group and 49 in the late-metastasis group. First-line treatment efficacy (P=0.004), OS (P<0.001), and progression-free survival (PFS) (P=0.006) were higher in the late-metastasis group. Kaplan-Meier curves revealed that the late-metastasis group had longer OS, intracranial progression-free survival (IPFS), and PFS (all P<0.001). Multivariate analysis showed that gender, Karnofsky performance status (KPS), efficacy of first-line treatment, radiotherapy, and brain metastasis at initial visit were significantly related to OS., Conclusions: Participants with pulmonary adenocarcinoma and brain metastasis at their initial visit had shorter OS and PFS than those who developed brain metastasis later. The efficacy of first-line treatment was related to OS while female gender and high KPS score were protective factors.