Salidroside induces mitochondrial dysfunction and ferroptosis to inhibit melanoma progression through reactive oxygen species production.

Reactive oxygen species (ROS) induces necroptotic and ferroptosis in melanoma cells. Salidroside (SAL) regulates ROS in normal cells and inhibits melanoma cell proliferation. This study used human malignant melanoma cells treated with SAL either alone or in combination with ROS scavenger (NAC) or ferroptosis inducer (Erastin). Through cell viability, wound healing assays, and a Seahorse analyze found that SAL inhibited cell proliferation, migration, extracellular acidification rate, and oxygen consumption rate. Metabolic flux analysis, complexes I, II, III, and IV activity of the mitochondrial respiratory chain assays, mitochondrial membrane potential assay, mitochondrial ROS, and transmission electron microscope revealed that SAL induced mitochondrial dysfunction and ultrastructural damage. Assessment of malondialdehyde, lipid ROS, iron content measurement, and Western blot analysis showed that SAL activated lipid peroxidation and promoted ferroptosis in A-375 cells. These effects were abolished after NAC treatment. Additionally, SAL and Erastin both inhibited cell proliferation and promoted cell death; SAL increased the Erastin sensitivity of cells while NAC antagonized it. In xenograft mice, SAL inhibited melanoma growth and promoted ROS-dependent ferroptosis. SAL induced mitochondrial dysfunction and ferroptosis to block melanoma progression through ROS production, which offers a scientific foundation for conducting SAL pharmacological research in the management of melanoma.

Analysis of the impact of the Xiaolangdi Reservoir on the runoff of the Yellow River downstream based on CEEMDAN-multiscale information entropy.

Water resources are vital to the development of human society, and mastering the law of runoff changes is the basis for achieving sustainable use of water resources. To study the impact of reservoir construction on the changes of downstream river runoff, this paper decomposes the runoff before and after reservoir construction using the CEEMDAN method based on the runoff data from the Huayuankou hydrological station. The fluctuation characteristics of each decomposition series of runoff before and after reservoir construction and the intra-annual variation pattern of runoff are also analyzed by combining multi-time information entropy and coefficient of variation. The results show that after the operation of the Xiaolangdi Reservoir, the annual runoff variation cycle tends to be flat, and the monthly runoff cycle is significantly reduced. After reservoir construction, the entropy values of each IMF and Res of runoff become larger, the complexity and randomness of runoff changes increase, and predictability decreases. Before and after the operation of the Xiaolangdi Reservoir, the coefficient of variation of runoff were 0.28-1 and 0.38-0.83, the distribution of runoff was more uniform, and the percentage of runoff in the flood season was reduced from 51.51 to 39.89%.

Daily runoff prediction during flood seasons based on the VMD-HHO-KELM model.

Improving the accuracy of daily runoff in the lower Yellow River is important for flood control and reservoir scheduling in the lower Yellow River. Influenced by factors such as meteorology, climate change, and human activities, runoff series present non-stationary and non-linear characteristics. To weaken the non-linearity and non-smoothness of runoff time series and improve the accuracy of daily runoff prediction, a new combined runoff prediction model (VMD-HHO-KELM) based on the ensemble Variational Modal Decomposition (VMD) algorithm and Harris Hawk Optimisation (HHO) algorithm-optimised Kernel Extreme Learning Machine (KELM) is proposed and applied to Gaocun and Lijin hydrological stations. The VMD-HHO-KELM model has the highest prediction accuracy, with the prediction model R2 reaching 0.95, mean absolute error reaching 13.3, and root mean square error reaching 33.83 at the Gaocun hydrological station, and R2 reaching 0.96, mean absolute error reaching 8.03, and root mean square error reaching 38.45 at the Lijin hydrological station.

A coupled CEEMD-BiLSTM model for regional monthly temperature prediction.

Temperature is an important indicator of climate change. With the gradual increase of global warming, a well-chosen model can improve the accuracy of temperature prediction. It is of great significance and value for future disaster prevention and mitigation and economic development. Monthly temperature is influenced by solar activity, monsoon, and other factors, with significant uncertainty, ambiguity, and randomness. A coupled CEEMD-BiLSTM temperature model is constructed based on the good decomposition-reconstruction characteristics of CEEMD for uncertain time series and the advantages of BiLSTM for solving stochastic prediction, and it is applied to the prediction of monthly temperature in Zhengzhou City. The results show that the minimum relative error of the coupled CEEMD-BiLSTM model is 0.01%, the maximum relative error is 0.99%, and the average relative error is 0.22%, and the prediction accuracy of this coupled model for monthly temperature in Zhengzhou is higher than that of the CEEMD-LSTM model, EEMD-BiLSTM model, and BP neural network model, with better stability and adaptability.

Ecological sensitivity study of the South-North Water Transfer central line water source area based on land use change.

Land use change and ecological sensitivity studies are relevant to the dynamic stability of the overall regional ecological environment. In this study, Nanyang City, a South-North Water Transfer water source area, was used as the study area to analyse land use changes and landscape pattern changes in Nanyang City from 1990 to 2020 based on land use data. Hierarchical analysis (AHP method) was used and combined with six sensitivity factors to conduct a multi-factor comprehensive ecological sensitivity evaluation of Nanyang City. The results show that: (1) between 1990 and 2020, the transfer of water and construction land in Nanyang City was larger, increasing by 30.25% and 99.56% respectively, with a small decrease in the area of cultivated land and a small increase in the area of forest land; the overall rate of land use change in Nanyang City during the 30-year period was first slow and then fast. (2) At the level of patch types, the fragmentation of cultivated land and construction land is the highest; during the study period, the overall fragmentation of the study area tends to decrease; at the level of landscape, each landscape type develops in the direction of equilibrium. (3) The ecological sensitivity increases gradually from the urban cluster in the central plain area to the periphery, with the highly sensitive areas distributed in the water area, the medium sensitive areas in the mountainous area, and the low sensitive areas and insensitive areas in the cultivated land and town planning area.

Characteristics of ecosystem service values in response to strong human activities in water sources of the South-to-North Water Diversion Middle Route in China.

A systematic grasp of the evolution of the spatial and temporal patterns of ecosystem service value (ESV) in the Central Line Project for South-to-North Water Diversion (CLPSNWD) water source area is conducive to deepening the ecological protection and promoting high-quality development of the water source area. In this paper, the dynamically adjusted equivalent factor method is used to reveal the spatial and temporal evolution of ESV in the water source area under strong human activities from 1991 to 2020. The results show that (1) during the 30-year period, urban point expansion increased the construction land area by 63.66 km2, and the degree of fragmentation increased. The water area increased the most, reaching 209.43 km2. (2) The total increase in ESV over the 30-year period was $1434 million, with forests and water accounting for the largest increase, i.e., 98% of the total increase in value. Among the individual service functions, hydrologic regulation generated the most significant service value.

Multi-spectral radiation thermometry based on an Alpha spectrum-LM algorithm under the background of high temperature and intense reflection.

In order to meet the needs of multi-spectral radiation temperature measurement under high temperature background, this paper studies the problems of reflected radiation interference and spectral emissivity difficult to obtain in high temperature and intense reflection environment. First, using discrete triangular surface elements and radiation angle coefficients, an analysis model of high temperature background reflected radiation is constructed to describe the variation characteristics of high temperature background reflected radiation. Secondly, the least squares support vector machine (LSSVM) is optimized by particle swarm optimization (PSO) algorithm, and an emissivity model identification algorithm based on Alpha spectrum-Levenberg Marquarelt (LM) algorithm is proposed, which has stronger applicability and accuracy than existing emissivity model identification methods. Finally, the high temperature background radiation and the emissivity model are combined to construct and solve the multi-spectral target equation, so as to realize the reflected radiation error correction and radiation temperature measurement under the high temperature and intense reflection background. The simulation and experimental comparison with the existing methods show that the temperature measurement error of the radiation temperature measurement method proposed in this paper is below 9.5K, which can effectively correct the reflected radiation error and further improve the temperature measurement accuracy.

Industrial water consumption forecasting based on combined CEEMD-ARIMA model for Henan province, central chain: A case study.

Industrial water consumption is a major component of the total regional water consumption. Accurate and scientific prediction of industrial water consumption is an essential guide to the rational use of natural resources. In this paper, we proposed a combined model of CEEMD (collective empirical modal decomposition) and ARIMA (autoregressive integrated moving average) for forecasting industrial water consumption to establish an accurate and efficient forecasting model, because of the poor generalization ability of most current industrial water consumption forecasting models. The influencing factors of industrial water consumption are complex, and the data are non-stationary. "Decomposition-prediction-reconstruction" is one of the significant methods for forecasting time series data, and the data decomposition has a suppressive influence on the modal mixing problem in the EMD decomposition procedure. Based on the smoothing ability of CEEMD for non-smooth signals and the better adaptation of the autoregressive moving average prediction model (ARIMA), a combined CEEMD-ARIMA model was established for industrial water consumption forecasting. This study was conducted for industrial water consumption in Henan Province in central China. The results suggest the combined CEEMD-ARIMA model has a favorable forecasting effect, with an average relative percentage error of 1.96%, and mean square error (MSE) of 0.35, a Nash efficiency coefficient (NSE) of 0.95, a prediction pass rate of 100%, and a better prediction accuracy than the ARIMA model and the combined EEMD-ARIMA model. It provides an effective prediction method for the prediction of industrial water consumption and has good application prospects.

Assessment of the value of regional water conservation services based on SWAT model.

The quantitative evaluation of water conservation in the Luoyang area can provide a basis for decision-making on regional water resources development and utilization, ecological environmental protection, and economic development planning. Based on the SWAT model and alternative engineering method, the water conservation and its service value in Luoyang region from 2009 to 2018 were assessed and the reasons for their spatial and temporal changes were analyzed. The results show that during the period of 2009-2018, the total water connotation and its service value reached the highest in 2014, with 16,927,100 m3 and 103 million yuan, respectively; the total water connotation and its service value reached the lowest in 2011, with 7,073,500 m3 and 43,224,000 yuan, respectively. Forest ecosystems have a strong water retention and storage capacity, and the highest water conservation and service value. Precipitation is the most important factor influencing water conservation and service value. The value of water-supporting services per unit area of ecosystem in Luoyang area is forest, grassland, arable land, and urban in descending order.

Evaluation of wetland ecosystem services value of the yellow river delta.

Analyzing and evaluating the ecosystem service value of wetlands can provide technical support and theoretical basis for regional socio-economic development, ecological environmental protection, and other planning measures. Based on the factors of hydrology, meteorology, society, economy, resources, environment, and culture, the wetland ecosystem services value of Yellow River Delta (YRD) was evaluated by the method of functional value and equivalent factor, which has certain reference significance for future research. Two methods were used to calculate the ecosystem services value of YRD in 2016, and the results were $3.28 × 109 per year and $4.53 × 109 per year, respectively, and the regulation services accounted for 76.3% and 16.7%, respectively. Through comparative analysis of ecosystem services value from 2001 to 2016, the average proportion of regulation services was 51%. Regulation service is the leading function of wetland ecosystem of YRD. Equivalent factor method is more suitable for the assessment of wetland ecosystem service value of YRD in 2016. In terms of time, ecosystem services value tended to increase, with an average rate of $2.02 × 109 per year. In terms of space, it gradually increased from inland to shallow sea water. On the premise of rational development and utilization, it is predicted that the value of ecosystem services will continue to grow in the future.

Assessment of the value of ecosystem services in water sources of the South-North Water Diversion Central Project: the case of Dengzhou City, Henan Province.

Dengzhou City is the first ecological water recharge city after the commissioning of the South-North Water Diversion Project. A study on the ecological service value of Dengzhou City and its evolutionary characteristics can provide a theoretical basis for the water supply security of the Central Line Project and regional ecological environmental protection. Based on the ecosystem service value equivalent factor method, GIS, ENVI and GeoSOS-FLUS software were used to monetize the ecosystem service values of Dengzhou City in 2007, 2011, 2014, 2015 and 2020; analyze the spatial and temporal change characteristics under its land use change conditions and predict the regional ecosystem service values of Dengzhou City in 2025. The results show that since the completion and commissioning of the South-North Water Transfer Central Project in 2014, the value of ecosystem services in Dengzhou City has rapidly increased from US$3.792 billion to US$4.612 billion, and in 2025, the value of ecosystem services in Dengzhou City is expected to reach US$4.8 billion.

The renaissance of human skin organ culture: A critical reappraisal.

Human skin organ culture (hSOC) is a simple but highly instructive and clinically relevant skin research method. It has been used for decades to study the development, differentiation, and function as well as the response to wounding or test agents of intact human skin in the presence of its appendages and all resident cell populations. hSOC has also proven useful in toxicological and oncological studies and studies of skin aging (both chronological aging and photoaging), skin energy metabolism, skin immunology, pigmentation biology, and cutaneous (neuro-)endocrinology and neurobiology. The pathobiology and treatment of various dermatoses can also be assessed ex vivo by organ-culturing intact lesional human skin. In addition to morphological analyses by routine histochemistry, quantitative (immuno)histomorphometry has proven to be an excellent tool for quantitating and localizing protein expression patterns in defined skin compartments and distinct cell populations using a relatively small amount of precious human tissue. Finally, more recent technological advances, such as siRNA-mediated gene silencing and sensory reinnervation of hSOCs, have further extended the range of methodological applications for the ex vivo study of human skin; it has emerged as the ultimate preclinical assay system for investigative dermatology, including the testing of drugs, cosmeceuticals and nutraceuticals and more, and is just one step below human skin xenotransplant in vivo mouse models and clinical trials. Here, we critically review the renaissance and variety of hSOC assays, their applications and limitations, and we critically compare them with 3D skin "equivalent" assays. The review closes with perspectives on how this ancient but highly informative and physiologically relevant ex vivo skin research method may be further developed in the future.

The Preciseness in Diagnosing Thyroid Malignant Nodules Using Shear-Wave Elastography.

Our study aimed to identify more accurate results about the diagnostic role of shear-wave elastography (SWE) for thyroid malignant nodules through a meta-analysis. Potential articles were searched in PubMed, Embase, and the Cochrane Library databases. Overall sensitivity and specificity with 95% confidence intervals (CIs) was used to represent the diagnostic accuracy of SWE. Summary receiver operating characteristic (ROC) curve was constructed to illustrate the results. In addition, χ² and I² tests were performed to assess heterogeneity. A value of p≤0.05 indicated significant heterogeneity. All the analysis was conducted in Meta-DiSc version 1.4 software. Twenty studies were included in the analysis. There were a total of 2,907 patients and 3,397 thyroid nodules included in the meta-analysis. Overall sensitivity and specificity were 0.68 (95% CI: 0.66-0.70) and 0.85 (95% CI: 0.84-0.87), respectively. The results showed the area under curve (AUC) was 0.9041, suggesting high accuracy of SWE for differentiating benign and malignant thyroid nodules. SWE showed high accuracy in identifying thyroid malignant nodules, suggesting it could serve as a diagnostic biomarker in thyroid nodules.

Assessment model of ecoenvironmental vulnerability based on improved entropy weight method.

Assessment of ecoenvironmental vulnerability plays an important role in the guidance of regional planning, the construction and protection of ecological environment, which requires comprehensive consideration on regional resources, environment, ecology, society and other factors. Based on the driving mechanism and evolution characteristics of ecoenvironmental vulnerability in cold and arid regions of China, a novel evaluation index system on ecoenvironmental vulnerability is proposed in this paper. For the disadvantages of conventional entropy weight method, an improved entropy weight assessment model on ecoenvironmental vulnerability is developed and applied to evaluate the ecoenvironmental vulnerability in western Jilin Province of China. The assessing results indicate that the model is suitable for ecoenvironmental vulnerability assessment, and it shows more reasonable evaluation criterion, more distinct insights and satisfactory results combined with the practical conditions. The model can provide a new method for regional ecoenvironmental vulnerability evaluation.

Progressive Facial Ulcer: A Case Report of Pyoderma gangrenosum.

Pyoderma gangrenosum (PG) is a rare neutrophilic dermatosis characterized by rapidly developing and painful skin ulcers with distinctive features. As far as we are concerned, there is no previous case report on facial PG in East-Asia. In this case, we describe a case of a 79-year-old man with a 3-month history of progressive painful ulcers on his cheek and upper lip. Initial suspicion of atypical mycobacterium infection led to an ineffective treatment regimen. Comprehensive infectious testing yielded negative results, and a positive pathergy test indicated a potential diagnosis of PG. A skin biopsy confirmed the diagnosis, and the patient showed significant improvement with intravenous methylprednisolone and oral cyclosporine treatment. After three months, complete resolution of the lesions was achieved without recurrence. The case highlights the diagnostic challenges associated with PG, which is often misdiagnosed due to its resemblance to other conditions. Thorough evaluation is crucial to exclude alternative diagnoses, particularly cutaneous infections. Clinical morphology, tissue biopsy, and culture are essential for accurate diagnosis. The presence of pathergy, the development of new lesions following minor trauma, can also be a diagnostic clue.

A monthly temperature prediction based on the CEEMDAN-BO-BiLSTM coupled model.

Temperature as an important indicator of climate change, accurate temperature prediction has important guidance and application value for agricultural production, energy management and disaster warning. Based on the advantages of CEEMDAN model in effectively extracting the time-frequency characteristics of nonlinear and nonsmooth signals, BO algorithm in optimizing the objective function within a limited number of iterations, and BiLSTM model in revealing the connection between the current data, the previous data and the future data, a monthly average temperature prediction model based on CEEMDAN-BO-BiLSTM is established. A CEEMDAN-BO-BiLSTM-based monthly average temperature prediction model is developed and applied to the prediction of monthly average temperature in Jinan City, Shandong Province. The results show that the constructed monthly mean temperature prediction model based on CEEMDAN-BO-BiLSTM is feasible; the constructed CEEMDAN-BO-BiLSTM model has an average absolute error of 1.17, a root mean square error of 1.43, an average absolute percentage error of 0.31%, which is better than CEEMDAN-BiLSTM, EMD-BiLSTM, and BiLSTM models in terms of prediction accuracy and shows better adaptability; the constructed CEEMDAN-BO-BiLSTM model illustrates that the model is not over-modeled and adds complexity using Friedman's test and performance comparisons between model run speeds. The model provides insights for effective forecasting of monthly mean temperatures.

Study of ecosystem service functions in typical receiving areas of the South-to-North Water Diversion Central Route based on a set of long time series.

Hebi is located in the northern part of China's Henan Province and is a typical receiving area for China's South-to-North Water Diversion Project. The assessment of habitat quality and water yield over a long time series is important for evaluating the stability of ecosystem services in Hebi and other receiving areas and for maintaining ecological security and promoting sustainable development. This paper aims to evaluate and dynamically analyse habitat quality and water yield in Hebi, and analyses the characteristics of changes in spatial and temporal patterns of land cover types, habitat quality and water yield in Hebi over the past 20 years, using 2000, 2005, 2010, 2015 and 2020 as horizontal years. The results indicate that: (1) During the study period, the overall land use type in Hebi City has been constantly changing, with the most significant conversion from arable land to other land types; combined with its landscape pattern index, Hebi City has a general characteristic of significant landscape fragmentation and complexity in land use. (2) Habitat quality in Hebi shows an overall trend towards better development, with water availability decreasing and then increasing; the zoning of ecosystem services in Hebi is divided into three classes: superior, good and general, with the area covered by the superior and general classes expanding year by year. (3) Correlation analysis by SPSS software shows that the correlation between habitat quality and landscape pattern index is greater than the correlation between habitat quality and climate change. Additionally, the correlation between water availability and climate change is greater than the correlation between water availability and landscape pattern index.

A novel optimization rainfall coupling model based on stepwise decomposition technique.

Traditional decomposition integration models decompose the original sequence into subsequences, which are then proportionally divided into training and testing periods for modeling. Decomposition may cause data aliasing, then the decomposed training period may contain part of the test period data. A more effective method of sample construction is sought in order to accurately validate the model prediction accuracy. Semi-stepwise decomposition (SSD), full stepwise decomposition (FSD), single model semi-stepwise decomposition (SMSSD), and single model full stepwise decomposition (SMFSD) techniques were used to create the samples. This study integrates Variational Mode Decomposition (VMD), African Vulture Optimization Algorithm (AVOA), and Least Squares Support Vector Machine (LSSVM) to construct a coupled rainfall prediction model. The influence of different VMD parameters α is examined, and the most suitable stepwise decomposition machine learning coupled model algorithm for various stations in the North China Plain is selected. The results reveal that SMFSD is relatively the most suitable tool for monthly precipitation forecasting in the North China Plain. Among the predictions for the five stations, the best overall performance is observed at Huairou Station (RMSE of 18.37 mm, NSE of 0.86, MRE of 107.2%) and Jingxian Station (RMSE of 24.74 mm, NSE of 0.86, MRE of 51.71%), while Hekou Station exhibits the poorest performance (RMSE of 25.11 mm, NSE of 0.75, MRE of 173.75%).