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Abstract Chimeric antigen receptor (CAR) T-cells targeting Fibroblast Growth Factor Receptor 4 (FGFR4), a highly expressed surface tyrosine receptor in rhabdomyosarcoma (RMS), are already in the clinical phase of development, but tumour heterogeneity and suboptimal activation might hamper their potency. Here we report an optimization strategy of the co-stimulatory and targeting properties of a FGFR4 CAR. We replace the CD8 hinge and transmembrane domain and the 4-1BB co-stimulatory domain with those of CD28. The resulting CARs display enhanced anti-tumor activity in several RMS xenograft models except for an aggressive tumour cell line, RMS559. By searching for a direct target of the RMS core-regulatory transcription factor MYOD1, we identify another surface protein, CD276, as a potential target. Bicistronic CARs (BiCisCAR) targeting both FGFR4 and CD276, containing two distinct co-stimulatory domains, have superior prolonged persistent and invigorated anti-tumor activities compared to the optimized FGFR4-specific CAR and the other BiCisCAR with the same 4-1BB co-stimulatory domain. Our study thus lays down the proof-of-principle for a CAR T-cell therapy targeting both FGFR4 and CD276 in RMS.

Abstract Accurate power load forecasting is crucial for the sustainable operation of smart grids. However, the complexity and uncertainty of load, along with the large-scale and high-dimensional energy information, present challenges in handling intricate dynamic features and long-term dependencies. This paper proposes a computational approach to address these challenges in short-term power load forecasting and energy information management, with the goal of accurately predicting future load demand. The study introduces a hybrid method that combines multiple deep learning models, the Gated Recurrent Unit (GRU) is employed to capture long-term dependencies in time series data, while the Temporal Convolutional Network (TCN) efficiently learns patterns and features in load data. Additionally, the attention mechanism is incorporated to automatically focus on the input components most relevant to the load prediction task, further enhancing model performance. According to the experimental evaluation conducted on four public datasets, including GEFCom2014, the proposed algorithm outperforms the baseline models on various metrics such as prediction accuracy, efficiency, and stability. Notably, on the GEFCom2014 dataset, FLOP is reduced by over 48.8%, inference time is shortened by more than 46.7%, and MAPE is improved by 39%. The proposed method significantly enhances the reliability, stability, and cost-effectiveness of smart grids, which facilitates risk assessment optimization and operational planning under the context of information management for smart grid systems.

Study region: The Daliang Mountain region, characterized by its widespread debris flow-pone catchments, is the primary sediment source area for the upper reaches of the Yangtze River, and has experienced intensive human activity over the past half-century. Study focus: Here, we combined lake deposits with sediment source areas to quantify the sediment source and corresponding sediment yield (SY) in response to recent human impacts in a typical debris flow-prone catchment located in the Daliang Mountain region, Southwest China. The fingerprinting techniques, incorporating geochemical elements and their specific ratios, were used to characterize the sediment provenances and corresponding SY. New hydrological insight for the region: The results indicated that gully erosion was the major sediment provenance (90.10 %) in the catchment, followed by cultivated land (6.76 %) and forested land (3.14 %) for the studied period. The temporal variations of SY showed two distinctive erosional stages in response to different human activities over the past 70 years, namely 1950−2004 and 2004−2020. Greater SY values, dominated by gully erosion, occurred from 1950 to 2004, implying that both critical national activities and revegetation projects have limited effects on surface sediment generation. In contrast, gully activity and resulting SY have sharply decreased since 2004 following the implementation of check dams. These comparisons indicate a central role of the check dam in reducing gully activity. The findings have important implications for policymakers to optimize the spatial layout of future soil conservation strategies in the region.

Abstract Stochasticity plays a significant role in the low‐power operation of a biological neural network. In an artificial neural network, stochasticity also contributes to critical functions such as the uncertainty quantification (UQ) for estimating the probability for the correctness of prediction. This UQ is vital for cutting‐edge applications, including medical diagnostics, autopilots, and large language models. Thanks to nonlinear variation of analogous Hall resistance with high computing velocity and low dissipation, a stochastic spin‐orbit‐torque (SOT) device exhibits significant potential for implementing the UQ. However, up until now, the application of UQ for stochastic SOT devices remains unexplored. In this study, based on SOT‐induced stochastic magnetic domain wall (DW) motion with varying velocity, a SOT synapse is fabricated that can emulate stochastic weight update following the Spike‐Timing‐Dependent‐Plasticity (STDP) rule. Furthermore, a stochastic SNN is set up, which, when compared to its deterministic counterpart, demonstrates a clear advantage in quantifying uncertainty for diagnosing the type of breast tumor (benign or malignant).

Abstract Fusion-positive rhabdomyosarcoma (FP-RMS) is an aggressive pediatric sarcoma driven primarily by the PAX3-FOXO1 fusion oncogene, for which therapies targeting PAX3-FOXO1 are lacking. Here, we screen 62,643 compounds using an engineered cell line that monitors PAX3-FOXO1 transcriptional activity identifying a hitherto uncharacterized compound, P3FI-63. RNA-seq, ATAC-seq, and docking analyses implicate histone lysine demethylases (KDMs) as its targets. Enzymatic assays confirm the inhibition of multiple KDMs with the highest selectivity for KDM3B. Structural similarity search of P3FI-63 identifies P3FI-90 with improved solubility and potency. Biophysical binding of P3FI-90 to KDM3B is demonstrated using NMR and SPR. P3FI-90 suppresses the growth of FP-RMS in vitro and in vivo through downregulating PAX3-FOXO1 activity, and combined knockdown of KDM3B and KDM1A phenocopies P3FI-90 effects. Thus, we report KDM inhibitors P3FI-63 and P3FI-90 with the highest specificity for KDM3B. Their potent suppression of PAX3-FOXO1 activity indicates a possible therapeutic approach for FP-RMS and other transcriptionally addicted cancers.

Background/Aims Although the conversion from tacrolimus (TAC) to cytotoxic T-lymphocyte-associated antigen 4-immunoglobulin (CTLA4-Ig) is effective in reducing TAC-induced nephrotoxicity, it remains unclear whether CTLA4-Ig has a direct effect on TAC-induced renal injury. In this study, we evaluated the effects of CTLA4-Ig on TAC-induced renal injury in terms of oxidative stress. Methods in vitro study was performed to assess the effect of CTLA4-Ig on TAC-induced cell death, reactive oxygen species (ROS), apoptosis, and the protein kinase B (AKT)/forkhead transcription factor (FOXO) 3 pathway in human kidney 2 cells. In the in vivo study, the effect of CTLA4-Ig on TAC-induced renal injury was evaluated using renal function, histopathology, markers of oxidative stress (8-hydroxy-2’-deoxyguanosine) and metabolites (4-hydroxy-2-hexenal, catalase, glutathione S-transferase, and glutathione reductase), and activation of the AKT/FOXO3 pathway with insulin-like growth factor 1 (IGF-1). Results CTLA4-Ig significantly decreased cell death, ROS, and apoptosis caused by TAC. TAC treatment increased apoptotic cell death and apoptosis-related proteins (increased Bcl-2-associated X protein and caspase-3 and decreased Bcl-2), but it was reversed by CTLA4-Ig treatment. The activation of p-AKT and p-FOXO3 by TAC decreased with CTLA4-Ig treatment. TAC-induced renal dysfunction and oxidative marker levels were significantly improved by CTLA4-Ig in vivo. Concomitant IGF-1 treatment abolished the effects of CTLA4-Ig. Conclusions CTLA4-Ig has a direct protective effect on TAC-induced renal injury via the inhibition of AKT/FOXO3 pathway.

Algal–bacterial symbiotic system is ubiquitous in natural water and has an important impact on water quality and environment such as algal toxins from extracellular secretions. In general, the species diversity and abundance of this system can be dynamically regulated by quorum sensing (QS). However, very little is known about extracellular secretions of algal–bacterial symbiotic system under the QS process. In this study, the effects of N-acylhomoserine lactones (AHLs) on the algal–bacterial symbiotic system were investigated. When the supplemental concentration was between 250 and 500 μg/L, the biological dry weight, Chl-a, and phycocyanin of algae cells and the fluorescence intensity of extracellular humic acid and fulvic acid increased greatly. Whereas, when the supplemental concentration was greater than 750 μg/L, the concentration of Chl-a and phycocyanin showed opposite patterns. This result indicates that AHLs can mediate communication between algae cells and bacteria, and bacteria can regulate the growth of algae by secreting signal molecules. The results of this study also provide useful information for blue-green algae outbreaks prediction by changing trend of AHLs in water. HIGHLIGHTS The amount of endogenous AHLs is closely related to algal growth.; The exogenous AHLs can regulate algae-bacterial symbiotic system.; The changing trend of AHLs in water may predict blue-green algae outbreaks.;

Cyanobacterial blooms (CBs) are a growing concern for shallow plateau lakes, and numerous studies have investigated the relationship between CBs and meteorological factors. However, these studies have typically lacked comprehensive analyses and neglected the impact of lag effects. This study employed Landsat satellite imagery to extract CBs information from Xingyun Lake from 1990 to 2019 and conducted a lag correlation analysis between meteorological factors ranging from 1 to 30 days with a 1-day step and CBs. The result show that the Sunshine Duration displayed a negative correlation with CBs at an 8-day lag, but when Sunshine Duration was

Abstract End-stage renal disease (ESRD) results in hippocampal volume reduction, but the hippocampal subfields atrophy patterns cannot be identified. We explored the volumes and asymmetry of the hippocampal subfields and their relationships with memory function and biochemical changes. Hippocampal global and subfields volumes were derived from 33 ESRD patients and 46 healthy controls (HCs) from structural MRI. We compared the volume and asymmetric index of each subfield, with receiver operating characteristic curve analysis to evaluate the differentiation between ESRD and HCs. The relations of hippocampal subfield volumes with memory performance and biochemical data were investigated in ESRD group. ESRD patients had smaller hippocampal subfield volumes, mainly in the left CA1 body, left fimbria, right molecular layer head, right molecular layer body and right HATA. The right molecular layer body exhibited the highest accuracy for differentiating ESRD from HCs, with a sensitivity of 80.43% and specificity of 72.73%. Worse learning process (r = 0.414, p = 0.032), immediate recall (r = 0.396, p = 0.041) and delayed recall (r = 0.482, p = 0.011) was associated with left fimbria atrophy. The left fimbria volume was positively correlated with Hb (r = 0.388, p = 0.05); the left CA1 body volume was negatively correlated with Urea (r = − 0.469, p = 0.016). ESRD patients showed global and hippocampal subfields atrophy. Left fimbria atrophy was related to memory function. Anemia and Urea level may be associated with the atrophy of left fimbria and CA1 body, respectively.

This paper addresses the distributed secure consensus problem for linear multi-agent systems (MAS) with unmeasurable states and Denial-of-Service (DoS) attacks. The observer is designed to be used in estimating unmeasurable states of agents. Then, an observer-based distributed event-triggered control protocol is proposed to save network resources. By using the piecewise Lyapunov function approach, several sufficient conditions for ensuring secure consensus are obtained. Further, a rigorous theoretical analysis shows that the given event-triggering scheme exhibits no Zeno behavior. Finally, the effectiveness of the proposed method is verified by numerical simulation.

Abstract Background Acute pancreatitis (AP) with critical illness is linked to increased morbidity and mortality. Current risk scores to identify high-risk AP patients have certain limitations. Objective To develop and validate a machine learning tool within 48 h after admission for predicting which patients with AP will develop critical illness based on ubiquitously available clinical, laboratory, and radiologic variables. Methods 5460 AP patients were enrolled. Clinical, laboratory, and imaging variables were collected within 48 h after hospital admission. Least Absolute Shrinkage Selection Operator with bootstrap method was employed to select the most informative variables. Five different machine learning models were constructed to predictive likelihood of critical illness, and the optimal model (APCU) was selected. External cohort was used to validate APCU. APCU and other risk scores were compared using multivariate analysis. Models were evaluated by area under the curve (AUC). The decision curve analysis was employed to evaluate the standardized net benefit. Results Xgboost was constructed and selected as APCU, involving age, comorbid disease, mental status, pulmonary infiltrates, procalcitonin (PCT), neutrophil percentage (Neu%), ALT/AST, ratio of albumin and globulin, cholinesterase, Urea, Glu, AST and serum total cholesterol. The APCU performed excellently in discriminating AP risk in internal cohort (AUC = 0.95) and external cohort (AUC = 0.873). The APCU was significant for biliogenic AP (OR = 4.25 [2.08–8.72], P

Diabetes mellitus is a metabolic disease with a high prevalence worldwide, and cardiovascular complications are the leading cause of mortality in patients with diabetes. Diabetic cardiomyopathy (DCM), which is prone to heart failure with preserved ejection fraction, is defined as a cardiac dysfunction without conventional cardiac risk factors such as coronary heart disease and hypertension. Mitochondria are the centers of energy metabolism that are very important for maintaining the function of the heart. They are highly dynamic in response to environmental changes through mitochondrial dynamics. The disruption of mitochondrial dynamics is closely related to the occurrence and development of DCM. Mitochondrial dynamics are controlled by circadian clock and show oscillation rhythm. This rhythm enables mitochondria to respond to changing energy demands in different environments, but it is disordered in diabetes. In this review, we summarize the significant role of circadian clock-controlled mitochondrial dynamics in the etiology of DCM and hope to play a certain enlightening role in the treatment of DCM.

Abstract The linearity and heteroscedasticity are the important characteristics of short‐term traffic flow data. Generally, the autoregressive integrated moving average (ARIMA) model and the generalized autoregressive conditional heteroscedasticity (GARCH) model are respectively used to explain these characteristics. However, the prerequisite for the use of ARIMA is that the training residuals should follow the standard Gaussian distribution, which is hard to be satisfied in practice. Meanwhile, the variance in the GARCH model usually neglects the time‐varying characteristic. To address these problems, this paper proposes an innovative method based on the combination of ARIMA, maximum correntropy criterion (MCC), conditional kernel density estimation (CKDE), and GARCH. Specifically, the MCC method is first employed to estimate the coefficients of the ARIMA model (i.e. ARIMA‐MCC), by which the linear prediction is conducted. Then, the CKDE model is established to describe the training residuals obtained by ARIMA‐MCC and estimate the time‐varying variance in the GARCH model (i.e. GARCH‐CKDE). Case studies based on four groups of data measured in the urban road are used to evaluate the performance of the proposed method. Compared with the traditional ARIMA model, the improvement by the proposed method reaches 14.45% in terms of the evaluation criterion of mean absolute percentage error.

Rhabdomyosarcoma (RMS) is a pediatric malignancy of skeletal muscle lineage with an aggressive subtype caused by translocations involving PAX3- /PAX7-FOXO1 chimeric transcription factors. Here the authors show that the BRG1-containing BAF complex is overexpressed and acts largely independently of the PAX3-FOXO1 chimera on chromatin to result in a myogenic differentiation blockade in this malignancy.

Chimeric antigen receptor (CAR) T cell therapies targeting single antigens have performed poorly in clinical trials for solid tumors due to heterogenous expression of tumor-associated antigens (TAAs), limited T cell persistence, and T cell exhaustion. Here, we aimed to identify optimal CARs against glypican 2 (GPC2) or CD276 (B7-H3), which were highly but heterogeneously expressed in neuroblastoma (NB), a lethal extracranial solid tumor of childhood. First, we examined CAR T cell expansion in the presence of targets by digital droplet PCR. Next, using pooled competitive optimization of CAR by cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), termed P-COCC, we simultaneously analyzed protein and transcriptome expression of CAR T cells to identify high-activity CARs. Finally, we performed cytotoxicity assays to identify the most effective CAR against each target and combined the CARs into a bicistronic “OR” CAR (BiCisCAR). BiCisCAR T cells effectively eliminated tumor cells expressing GPC2 or CD276. Furthermore, the BiCisCAR T cells demonstrated prolonged persistence and resistance to exhaustion when compared with CARs targeting a single antigen. This study illustrated that targeting multiple TAAs with BiCisCAR may overcome heterogenous expression of target antigens in solid tumors and identified a potent, clinically relevant CAR against NB. Moreover, our multimodal approach integrating competitive expansion, P-COCC, and cytotoxicity assays is an effective strategy to identify potent CARs among a pool of candidates.

Psathyrostachys huashanica Keng (2n = 2x = 14, NsNs) is an excellent gene resource for wheat breeding, which is characterized by early maturity, low plant height, and disease resistance. The wheat-P. huashanica derivatives were created by the elite genes of P. huashanica and permeate into common wheat through hybridization. Among them, a long-glume material 20JH1155 was identified, with larger grains and longer spike than its parents. In the present study, the methods of cytological observation, GISH, and sequential FISH analysis showed that 20JH1155 contained 21 pairs of wheat chromosomes and a pair of P. huashanica. There were some differences in 5A and 7B chromosomes between 20JH1155 and parental wheat 7182. Molecular marker, FISH, and sequence cloning indicated 20JH1155 alien chromosomes were 3Ns of P. huashanica. In addition, differentially expressed genes during immature spikelet development of 20JH1155 and 7182 and predicted transcription factors were obtained by transcriptome sequencing. Moreover, a total of 7 makers derived from Ph#3Ns were developed from transcriptome data. Taken together, the wheat-P. huashanica derived line 20JH1155 provides a new horizon on distant hybridization of wheat and accelerates the utilization of genes of P. huashanica.

In order to improve the analytical result and robustness of modulation signal bispectrum based sideband estimator （MSB-SE）， a method for extracting wear characteristics combining wavelet packet energy （WPE） and MSB-SE is proposed. Firstly， the wavelet packet transform is used to decompose the signal into multiple frequency bands， and the WPE of each frequency band is calculated. The frequency band with higher energy is selected for reconstruction to optimize the analysis frequency band and reduce the calculation amount. Then， the MSB-SE is carried out to extract the characteristics of tooth surface wear， and the online monitoring of tooth surface wear damage state is realized by using a reasonable index. Simulation and experimental results show that the proposed method is more robust， and can more accurately monitor tooth surface wear and evaluate the degree of wear damage.

The organic-rich shales and mudstones of the Middle Permian are the most important unconventional petroleum targets in the southern Junggar Basin of northwestern China. Although numerous studies have been vigorously conducted on paleoenvironment reconstructions, the organic matter enrichment mechanism is still controversial due to the utilization of problematic geochemical proxies established in early studies. In this study, major and trace elemental compositions, molecular markers, stable carbon isotopic compositions, and organic petrology were used to study multiple factors affecting the accumulation of organic matter in sediments. According to the results, a relatively hydrostatic, brackish, anoxic environment is proposed in the northern periphery of the Bogda Mountain, where the original structure of organic matter could be preserved with non-correlations between the productivity proxies (P and Ba) and TOC. In the western Bogda area, organic-rich sediments were deposited under suboxic conditions, with frequent fluctuation occurring between the top and bottom water columns. The accumulation of organic matter was the result of productivity blooms and rapid sedimentation. This improved study of the enrichment of organic matter in the Middle Permian around the Bogda Mountain can contribute to improved evaluations of the petroleum potential and distinguishing the characteristics of different organic matter enrichment models.

As essential environmental parameters in the greenhouse, appropriate light and CO2 will improve agricultural productivity and quality. Although many related studies have been carried out on the intelligent regulation of these environmental factors, the regulation of light and CO2 is usually controlled separately, and energy consumption is rarely considered. This paper proposed a coordinated control strategy for greenhouse light and CO2 based on the multi-objective optimization model. Firstly, the experiments on the net photosynthetic rate of blueberry under different temperatures, photon flux density, and CO2 concentration nesting were carried out to establish a blueberry net photosynthetic rate prediction model based on Support Vector Regression (SVR). Secondly, a model for calculating the energy cost of both light and CO2 was constructed. Thirdly, taking the maximum net photosynthetic rate and the minimum energy cost as the objective functions, the Non-dominated Sorting Genetic Algorithm (NSGA-II) was leveraged to obtain the Pareto optimal solutions of the target regulation values of light and CO2 concentration in different temperature ranges. Then, the optimal values were selected based on two different strategies. Finally, the multi-objective optimal control strategy proposed in this paper was compared with both the classical threshold control strategy and the Gaussian curvature maximization control strategy. The results indicated that the strategy which prioritized energy saving could reduce the energy cost by about 22.33% and 19.08%, respectively, under the premise that the net photosynthetic rate was consistent. Meanwhile, the strategy that prioritized production efficiency could increase the net photosynthetic rate by about 8.40% and 4.42%, respectively, with the same energy cost. In conclusion, the proposed multi-objective optimization control can improve the greenhouse climate control performance and reduce cost compared with other mentioned strategies.

It is crucial to understand the spatial-temporal variation of water quality for the water safety and eutrophication migration in plateau lakes. To identify the variation property and the main causes of eutrophication and continuous water quality deterioration, the water quality, including the water temperature (WT), dissolved oxygen (DO), pH, Chl-a, turbidity, total nitrogen (TN) and total phosphorus (TP), of Lake Xingyun was monitored from 2016 to 2021, and their spatial and temporal distribution characteristics were analyzed. The results show that there is no obvious thermal stratification in the vertical direction; pH and DO decrease with depth, which is caused by both physical and biochemical processes, especially at the bottom of Lake Xingyun, which has an anaerobic environment. The chlorophyll content was higher during the high-flow periods and varied significantly in the vertical direction; the spatial variation of water quality in Lake Xingyun was more obvious in the low-flow period and alkaline throughout the year. The average content of total phosphorus (TP) ranged between 0.33 and 0.53 mg/L during the high-flow periods and between 0.22 and 0.51 mg/L during the low-flow periods, while the average content of total nitrogen (TN) ranged between 1.92 and 2.62 mg/L and 1.36 and 2.53 mg/L during the high- and low-flow periods, respectively. The analysis of the inflow samples shows that exogenous nitrogen and phosphorus is the main pollution source affecting the nitrogen and phosphorus content of Lake Xingyun. The trophic level index (TLI) shows that Lake Xingyun is in eutrophication all year round, and even in areas less affected by the exogenous nutrient, there are still conditions for cyanobacterial blooms. This study shed new light on the water quality, eutrophication status and changes in Lake Xingyun, providing suggestions for controlling lake pollution and eutrophication mitigation.

Understanding the seasonal variation characteristics and trends in water quality is one of the most important aspects for protecting and conserving lakes. Lake Yangzong water quality parameters and nutrients, including water temperature, dissolved oxygen (DO), pH, conductivity, Chlorophyll-a, phycocyanin, total nitrogen (TN) and total phosphorus (TP), were monitored in different seasons from 2015 to 2021. Based on the monitoring data, the temporal and spatial variations of various parameters were analyzed. The results showed that Lake Yangzong is a warm monomictic lake. The Pearson correlation coefficient and correlation analysis showed water quality parameters were significantly correlated and probably affected by temperature. Cyanobacteria were at risk of blooming in spring and autumn. The contents of TN and TP in winter were significantly higher than in summer, especially TN, with both reaching a peak at the epilimnion and hypolimnion in December 2020 (TN = 1.3 mg/L, TP = 0.06 mg/L). We also observed a dual risk of endogenous release and exogenous input. Therefore, strengthening the supervision for controlling eutrophication caused by human activities and endogenous release is urgently needed.

Abstract In this study, using the Climate Model Intercomparison Project 5 (CMIP5) simulations and by empirical orthogonal function (EOF) analysis, the first mode of variability in interannual surface air temperature (SAT) in Antarctica (EOF1) was examined for the period between 1979–2004 and 2051–2099 during the austral summer. The ensemble mean of EOF1 of the CMIP5 models shows a positive SAT anomaly over the northern Antarctic Peninsula (AP) and a negative SAT anomaly over Eastern Antarctica (EA) in both periods. A poleward expansion of the AP positive anomaly and an increase in the negative anomaly over interior EA are expected in 2051–2099, resulting in a larger difference of interannual SAT between interior EA and the AP in 2051–2099 than in 1979–2004. The increasing difference in the interannual SAT is consistent with a larger magnitude of the SAM‐related circulation anomalies in the future.

According to the vertical section monitoring data of Lake Lugu water temperature (WT), electrical conductivity (EC), dissolved oxygen (DO), pH and chlorophyll-a (Chl-a) parameters in January (winter), April (spring), July (summer), and October (autumn) in 2015, the vertical stratification structure of WT and the null seasonality of water chemistry were analyzed. The relationship between the seasonal variation of WT stratification and the spatial and temporal distribution of EC, pH, DO and Chl-a was explored. The relationship between EC and WT was found for the epilimnion, thermocline and hypolimnion. The results of the study showed that: (1) The Lake Lugu water body shows obvious thermal stratification in spring, summer and autumn. In winter, the WT is close to isothermal condition in the vertical direction; in summer, the thermocline is located at 10–25 m water depth; while in autumn, the thermocline moves down to 20–30 m. (2) The Hypolimnion WT was maintained at 9.5 °C~10 °C, which is consistent with the annual mean temperature of Lake Lugu, indicating that the hypolimnion water column is stable and relatively constant, and reflects the annual mean temperature of the lake. The thermally stratified structure has some influence on the changes of EC, DO, pH and Chl-a, resulting in the obvious stratification of EC, DO and pH in the water body. (3) Especially in summer, when the temperature increased, the thermal stratification phenomenon was significant, and DO and pH peaked in thermocline, with a decreasing trend from the peak upward and downward, and the hypolimnion was in an anoxic state and the pH value was small. Although chlorophyll a remained low below thermocline and was not high overall, there was a sudden increase in the surface layer, which should be highly warned to prevent a large algal bloom or even a localized outbreak in Lake Lugu. (4) There is a simple linear function between EC and WT in both vertical section and Epilimnion, thermocline and hypolimnion, which proves that Lake Lugu is still influenced by natural climate and maintains natural water state, and is a typical warm single mixed type of lake. (5) It is suggested to strengthen water quality monitoring, grasp its change pattern and influence factors, and take scientific measures to prevent huge pressure on the closed ecological environment of Lake Lugu, and provide scientific basis for the protection of high-quality freshwater lakes in the plateau.

Understanding the spatiotemporal distributions and variation characteristics of water quality parameters is crucial for ecosystem restoration and management of lakes, in particular, Lake Qilu (QL), a typical plateau shallow lake on the Yunnan-Guizhou Plateau, southwestern China. To identify the main causes of harmful algal blooming and continuous water quality decline, the total phosphorus (TP), total nitrogen (TN), water temperature (WT), dissolved oxygen (DO), chlorophyll-a (Chl-a), pH, and turbidity in hypereutrophic Lake Qilu from January 2017 to December 2021 were analyzed. The results showed a complex pattern in spatiotemporal distribution and variation. WT showed no significant change in the vertical profile. DO and pH value variations were caused by both physical and biochemical processes, especially at the bottom of Lake QL with an anaerobic environment. The Trophic State Index (TSI) assessment results showed that Lake QL is a eutrophic (70.14% of all samples, 50 < TSI < 70) to a hypereutrophic lake (29.86%, 70 < TSI) with poor water quality (WQI < 25). TP and WT were the main factors controlling harmful algal blooms (HABs) based on the statistical analysis of Principal Component Analysis (PCA), Random Forest Model (RFM), and Correlation Analysis (CA). In lake QL, TP loading reduction and water level increase might be the key strategies for treating HABs in the future. Based on our results, reducing TP loading may be more effective than reducing TN to prevent HABs in the highly eutrophicated Lake Qilu.

Basal p53 levels are tightly suppressed under normal conditions. Disrupting this regulation results in elevated p53 levels to induce cell cycle arrest, apoptosis, and tumor suppression. Here, we report the suppression of basal p53 levels by a nuclear, p53-regulated long noncoding RNA that we termed PURPL (p53 upregulated regulator of p53 levels). Targeted depletion of PURPL in colorectal cancer cells results in elevated basal p53 levels and induces growth defects in cell culture and in mouse xenografts. PURPL associates with MYBBP1A, a protein that binds to and stabilizes p53, and inhibits the formation of the p53-MYBBP1A complex. In the absence of PURPL, MYBBP1A interacts with and stabilizes p53. Silencing MYBBP1A significantly rescues basal p53 levels and proliferation in PURPL-deficient cells, suggesting that MYBBP1A mediates the effect of PURPL in regulating p53. These results reveal a p53-PURPL auto-regulatory feedback loop and demonstrate a role for PURPL in maintaining basal p53 levels.

Future projection of changes in the East Asia Summer and Winter Monsoon are hindered by a lack of understanding of past variability. Here, using longterm transient simulations, the authors show that the monsoons respond in phase to precessional forcing, yet out of phase millennial-scale North Atlantic forcing.

Short-term traffic flow prediction is important to realize real-time traffic instruction. However, due to the existing strong nonlinearity and non-stationarity in short-term traffic volume data, it is hard to obtain a satisfactory result through the traditional method. To this end, this paper develops an innovative hybrid method based on the time varying filtering based empirical mode decomposition (TVF-EMD) and least square support vector machine (LSSVM). Specifically, TVF-EMD is firstly used to deal with the implied non-stationarity in the original data by decomposing them into several different subseries. Then, the LSSVM models are established for each subseries to capture the linear and nonlinear characteristics embedded in the original data, and the corresponding prediction results are superimposed to obtain the final one. Finally, case studies based on two groups of data measured from an arterial road intersection are employed to evaluate the performance of the proposed method. The experimental results indicate it outperforms the other involved models. For example, compared with the LSSVM model, the average improvements by the proposed method in terms of the indexes of mean absolute error, mean relative percentage error, root mean square error and root mean square relative error are 7.397, 15.832%, 10.707 and 24.471%, respectively.

Adoptive immunotherapy with antibody-based therapy or with T cells transduced to express chimeric antigen receptors (CARs) is useful to the extent that the cell surface membrane protein being targeted is not expressed on normal tissues. The most successful CAR-based (anti-CD19) or antibody-based therapy (anti-CD20) in hematologic malignancies has the side effect of eliminating the normal B cell compartment. Targeting solid tumors may not provide a similar expendable marker. Beyond antibody to Her2/NEU and EGFR, very few antibody-based and no CAR-based therapies have seen broad clinical application for solid tumors. To expand the way in which the surfaceome of solid tumors can be analyzed, we created an algorithm that defines the pairwise relative overexpression of surface antigens. This enables the development of specific immunotherapies that require the expression of two discrete antigens on the surface of the tumor target. This dyad analysis was facilitated by employing the Hotelling’s T-squared test (Hotelling–Lawley multivariate analysis of variance) for two independent variables in comparison to a third constant entity (i.e., gene expression levels in normal tissues). We also present a unique consensus scoring mechanism for identifying transcripts that encode cell surface proteins. The unique application of our bioinformatics processing pipeline and statistical tools allowed us to compare the expression of two membrane protein targets as a pair, and to propose a new strategy based on implementing immunotherapies that require both antigens to be expressed on the tumor cell surface to trigger therapeutic effector mechanisms. Specifically, we found that, for MYCN amplified neuroblastoma, pairwise expression of ACVR2B or anaplastic lymphoma kinase (ALK) with GFRA3, GFRA2, Cadherin 24, or with one another provided the strongest hits. For MYCN, non-amplified stage 4 neuroblastoma, neurotrophic tyrosine kinase 1, or ALK paired with GFRA2, GFRA3, SSK1, GPR173, or with one another provided the most promising paired-hits. We propose that targeting these markers together would increase the specificity and thereby the safety of CAR-based therapy for neuroblastoma.

The ITO (indium tin oxide) conductive glass-matrix CuS-GeO2-TiO2 composite coating was generated via EPD (electrophoretic deposition) and followed by a sintering treatment at 450°C for 40 minutes. Characterizations of the CuS-GeO2-TiO2 composite coating were taken by SEM (scanning electron microscope), XRD (X-ray diffraction), EDX (energy dispersive X-ray), UV-Vis DRS (ultraviolet-visible diffuse reflection spectrum), and FT-IR (Fourier transform infrared spectroscopy). Results showed that CuS and GeO2 had dispersed in this CuS-GeO2-TiO2 composite coating (mass percentages for CuS and GeO2 were 1.23% and 2.79%, respectively). The electrochemical studies (cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and Tafel polarization) of this CuS-GeO2-TiO2 composite coating electrode were performed in pH = 9.51 Na2CO3-NaHCO3 buffer solution containing 0.50 mol/L CH3OH under the conditions of visible light, ultraviolet light (λ = 365 nm), and dark (without light irradiation as control), respectively. Electrochemical studies indicated that this CuS-GeO2-TiO2 composite coating electrode had better photoelectrocatalytic activity than the pure TiO2 electrode in the electrocatalysis of methanol under visible light.

The Ewing sarcoma family of tumors (EFT) is a group of highly malignant small round blue cell tumors occurring in children and young adults. We report here the largest genomic survey to date of 101 EFT (65 tumors and 36 cell lines). Using a combination of whole genome sequencing and targeted sequencing approaches, we discover that EFT has a very low mutational burden (0.15 mutations/Mb) but frequent deleterious mutations in the cohesin complex subunit STAG2 (21.5% tumors, 44.4% cell lines), homozygous deletion of CDKN2A (13.8% and 50%) and mutations of TP53 (6.2% and 71.9%). We additionally note an increased prevalence of the BRCA2 K3326X polymorphism in EFT patient samples (7.3%) compared to population data (OR 7.1, p = 0.006). Using whole transcriptome sequencing, we find that 11% of tumors pathologically diagnosed as EFT lack a typical EWSR1 fusion oncogene and that these tumors do not have a characteristic Ewing sarcoma gene expression signature. We identify samples harboring novel fusion genes including FUS-NCATc2 and CIC-FOXO4 that may represent distinct small round blue cell tumor variants. In an independent EFT tissue microarray cohort, we show that STAG2 loss as detected by immunohistochemistry may be associated with more advanced disease (p = 0.15) and a modest decrease in overall survival (p = 0.10). These results significantly advance our understanding of the genomic and molecular underpinnings of Ewing sarcoma and provide a foundation towards further efforts to improve diagnosis, prognosis, and precision therapeutics testing.

Peptide nucleic acids (PNAs) have gained much interest as molecular recognition tools in biology, medicine and chemistry. This is due to high hybridization efficiency to complimentary oligonucleotides and stability of the duplexes with RNA or DNA. We have synthesized 15/16-mer PNA probes to detect the HER2 mRNA. The performance of these probes to detect the HER2 target was evaluated by fluorescence imaging and fluorescence bead assays. The PNA probes have sufficiently discriminated between the wild type HER2 target and the mutant target with single base mismatches. Furthermore, the probes exhibited excellent linear concentration dependence between 0.4 to 400 fmol for the target gene. The results demonstrate potential application of PNAs as diagnostic probes with high specificity for quantitative measurements of amplifications or over-expressions of oncogenes.

Neuroblastoma is one of the most genomically heterogeneous childhood malignances studied to date, and the molecular events that occur during the course of the disease are not fully understood. Genomic studies in neuroblastoma have showed only a few recurrent mutations and a low somatic mutation burden. However, none of these studies has examined the mutations arising during the course of disease, nor have they systemically examined the expression of mutant genes. Here we performed genomic analyses on tumors taken during a 3.5 years disease course from a neuroblastoma patient (bone marrow biopsy at diagnosis, adrenal primary tumor taken at surgical resection, and a liver metastasis at autopsy). Whole genome sequencing of the index liver metastasis identified 44 non-synonymous somatic mutations in 42 genes (0.85 mutation/MB) and a large hemizygous deletion in the ATRX gene which has been recently reported in neuroblastoma. Of these 45 somatic alterations, 15 were also detected in the primary tumor and bone marrow biopsy, while the other 30 were unique to the index tumor, indicating accumulation of de novo mutations during therapy. Furthermore, transcriptome sequencing on the 3 tumors demonstrated only 3 out of the 15 commonly mutated genes (LPAR1, GATA2, and NUFIP1) had high level of expression of the mutant alleles, suggesting potential oncogenic driver roles of these mutated genes. Among them, the druggable G-protein coupled receptor LPAR1 was highly expressed in all tumors. Cells expressing the LPAR1 R163W mutant demonstrated a significantly increased motility through elevated Rho signaling, but had no effect on growth. Therefore, this study highlights the need for multiple biopsies and sequencing during progression of a cancer and combinatorial DNA and RNA sequencing approach for systematic identification of expressed driver mutations.

Whether differentiation of induced pluripotent stem cells (iPSCs) in ischemic myocardium enhances their immunogenicity, thereby increasing their chance for rejection, is unclear. Here, we dynamically demonstrated the immunogenicity and rejection of iPSCs in ischemic myocardium using bioluminescent imaging (BLI). Murine iPSCs were transduced with a tri-fusion (TF) reporter gene consisting of firefly luciferase-red fluorescent protein-truncated thymidine kinase (fluc-mrfp-tTK). Ascorbic acid (Vc) were used to induce iPSCs to differentiate into cardiomyocytes (CM). iPSCs and iPS-CMs were intramyocardially injected into immunocompetent or immunosuppressed allogenic murine with myocardial infarction. BLI was performed to track transplanted cells. Immune cell infiltration was evaluated by immunohistochemistry. Syngeneic iPSCs were also injected and evaluated. The results demonstrated that undifferentiated iPSCs survived and proliferated in allogenic immunocompetent recipients early post-transplantation, accompanying with mild immune cell infiltration. With in vivo differentiation, a progressive immune cell infiltration could be detected. While transplantation of allogenic iPSC-CMs were observed an acute rejection from receipts. In immune-suppressed recipients, the proliferation of iPSCs could be maintained and intramyocardial teratomas were formed. Transplantation of syngeneic iPSCs and iPSC-CMs were also observed progressive immune cell infiltration. This study demonstrated that iPSC immunogenicity increases with in vivo differentiation, which will increase their chance for rejection in iPSC-based therapy.

BACKGROUND: Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. METHODOLOGY/PRINCIPAL FINDINGS: The Affymetrix platform was utilized to catalogue gene expression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were identified for each tissue and functional enrichment analysis revealed themes consistent with known physio-anatomic functions for each organ. In addition, a comparison of orthologous gene expression between matched canine and human normal tissues uncovered remarkable similarity. To demonstrate the utility of this dataset, novel canine gene annotations were established based on comparative analysis of dog and human tissue selective gene expression and manual curation of canine probeset mapping. Public access, using infrastructure identical to that currently in use for human normal tissues, has been established and allows for additional comparisons across species. CONCLUSIONS/SIGNIFICANCE: These data advance our understanding of the canine genome through a comprehensive analysis of gene expression in a diverse set of tissues, contributing to improved functional annotation that has been lacking. Importantly, it will be used to inform future studies of disease in the dog as a model for human translational research and provides a novel resource to the community at large.

This study aimed to analyze the changes associated with serum miRNAs in patients with cervical intraepithelial neoplasia (CIN) and cervical cancer in predicting early-stage cervical cancer. A total of 229 serum samples were collected to extract miRNAs. The expression level of miR-146b-5p, miR-192-5p and miR-122-5p were determined via qRT-PCR (Quantitative Real-time PCR), and their relative expressions were calculated using the equation: 2−∆∆Ct. We observed significantly higher expression levels of serum miR-146b-5p, miR-192-5p and miR-122-5p in the cervical diseases (CIN and cervical cancer) compared with controls. The expression levels of serum miR-146b5p, miR-192-5p and miR-122-5p in cervical cancer were significantly higher than in controls. The relative expressions of serum miR-146b-5p and miR-192-5p in CIN were significantly higher than controls. However, there was no difference in three miRNAs between CIN and cervical cancer. The relative expressions of serum miR-146b-5p in patients classified as FIGO (International Federation of Gynaecology and Obstetrics) stage I were significantly higher than in controls and CIN. The AUC (area under the ROC curve) of the three miRNAs combined with SCC (squamous cell carcinoma antigen) in diagnosing cervical cancer was 0.840, and the sensitivity and specificity were 0.632 and 0.957, respectively. Serum miR-146b-5p, miR-192-5p and miR-122-5p showed promising efficacy as noninvasive biomarkers to accurately diagnose cervical cancer and demonstrated certain early diagnostic values, especially miR-146b-5p and miR-192- 5p. The combined use of the three serum miRNAs with SCC could further improve the diagnostic efficiency for cervical cancer. [ABSTRACT FROM AUTHOR]

In the fiber winding process, strong disturbance, uncertainty, strong coupling, and fiber friction complicate the winding constant tension control. In order to effectively reduce the influence of these problems on the tension output, this paper proposed a tension fluctuation rejection strategy based on feedforward compensation. In addition to the bias harmonic curve of the unknown state, the tension fluctuation also contains the influence of bounded noise. A tension fluctuation observer (TFO) is designed to cancel the uncertain periodic signal, in which the frequency generator is used to estimate the critical parameter information. Then, the fluctuation signal is reconstructed by a third-order auxiliary filter. The estimated signal feedforward compensates for the actual tension fluctuation. Furthermore, a time-varying parameters fractional-order PID controller (TPFOPID) is realized to attenuate the bounded noise in the fluctuation. Finally, TPFOPID is enhanced by TFO and applied to control a tension control system considering multi-source disturbances. The stability of the method is analyzed by using the Lyapunov theorem. Finally, numerical simulations verify that the proposed scheme improves the tracking ability and robustness of the system in response to tension fluctuations. [ABSTRACT FROM AUTHOR]