An atlas of genetic effects on cellular composition of the tumor microenvironment.

Deciphering the composition of the tumor microenvironment (TME) is critical for understanding tumorigenesis and to design immunotherapies. In the present study, we mapped genetic effects on cell-type proportions using single-cell and bulk RNA sequencing data, identifying 3,494 immunity quantitative trait loci (immunQTLs) across 23 cancer types from The Cancer Genome Atlas. Functional annotation revealed regulatory potential and we further assigned 1,668 genes that regulate TME composition. We constructed a combined immunQTL map by integrating data from European and Chinese colorectal cancer (CRC) samples. A polygenic risk score that incorporates these immunQTLs and hits on a genome-wide association study outperformed in CRC risk stratification within 447,495 multiethnic individuals. Using large-scale population cohorts, we identified that the immunQTL rs1360948 is associated with CRC risk and prognosis. Mechanistically, the rs1360948-G-allele increases CCL2 expression, recruiting regulatory T cells that can exert immunosuppressive effects on CRC progression. Blocking the CCL2-CCR2 axis enhanced anti-programmed cell death protein 1 ligand therapy. Finally, we have established a database (CancerlmmunityQTL2) to serve the research community and advance our understanding of immunogenomic interactions in cancer pathogenesis.

Olfactory Diagnosis Model for Lung Health Evaluation Based on Pyramid Pooling and SHAP-Based Dual Encoders.

This study introduces a novel deep learning framework for lung health evaluation using exhaled gas. The framework synergistically integrates pyramid pooling and a dual-encoder network, leveraging SHapley Additive exPlanations (SHAP) derived feature importance to enhance its predictive capability. The framework is specifically designed to effectively distinguish between smokers, individuals with chronic obstructive pulmonary disease (COPD), and control subjects. The pyramid pooling structure aggregates multilevel global information by pooling features at four scales. SHAP assesses feature importance from the eight sensors. Two encoder architectures handle different feature sets based on their importance, optimizing performance. Besides, the model's robustness is enhanced using the sliding window technique and white noise augmentation on the original data. In 5-fold cross-validation, the model achieved an average accuracy of 96.40%, surpassing that of a single encoder pyramid pooling model by 10.77%. Further optimization of filters in the transformer convolutional layer and pooling size in the pyramid module increased the accuracy to 98.46%. This study offers an efficient tool for identifying the effects of smoking and COPD, as well as a novel approach to utilizing deep learning technology to address complex biomedical issues.

Overcoming the Limits of Cross-Sensitivity: Pattern Recognition Methods for Chemiresistive Gas Sensor Array.

As information acquisition terminals for artificial olfaction, chemiresistive gas sensors are often troubled by their cross-sensitivity, and reducing their cross-response to ambient gases has always been a difficult and important point in the gas sensing area. Pattern recognition based on sensor array is the most conspicuous way to overcome the cross-sensitivity of gas sensors. It is crucial to choose an appropriate pattern recognition method for enhancing data analysis, reducing errors and improving system reliability, obtaining better classification or gas concentration prediction results. In this review, we analyze the sensing mechanism of cross-sensitivity for chemiresistive gas sensors. We further examine the types, working principles, characteristics, and applicable gas detection range of pattern recognition algorithms utilized in gas-sensing arrays. Additionally, we report, summarize, and evaluate the outstanding and novel advancements in pattern recognition methods for gas identification. At the same time, this work showcases the recent advancements in utilizing these methods for gas identification, particularly within three crucial domains: ensuring food safety, monitoring the environment, and aiding in medical diagnosis. In conclusion, this study anticipates future research prospects by considering the existing landscape and challenges. It is hoped that this work will make a positive contribution towards mitigating cross-sensitivity in gas-sensitive devices and offer valuable insights for algorithm selection in gas recognition applications.

Enhancing prognostic prediction in hepatocellular carcinoma post-TACE: a machine learning approach integrating radiomics and clinical features.

Objective: This study aimed to investigate the use of radiomics features and clinical information by four machine learning algorithms for predicting the prognosis of patients with hepatocellular carcinoma (HCC) who have been treated with transarterial chemoembolization (TACE). Methods: A total of 105 patients with HCC treated with TACE from 2002 to 2012 were enrolled retrospectively and randomly divided into two cohorts for training (n = 74) and validation (n = 31) according to a ratio of 7:3. The Spearman rank, random forest, and univariate Cox regression were used to select the optimal radiomics features. Univariate Cox regression was used to select clinical features. Four machine learning algorithms were used to develop the models: random survival forest, eXtreme gradient boosting (XGBoost), gradient boosting, and the Cox proportional hazard regression model. The area under the curve (AUC) and C-index were devoted to assessing the performance of the models in predicting HCC prognosis. Results: A total of 1,834 radiomics features were extracted from the computed tomography images of each patient. The clinical risk factors for HCC prognosis were age at diagnosis, TNM stage, and metastasis, which were analyzed using univariate Cox regression. In various models, the efficacy of the combined models generally surpassed that of the radiomics and clinical models. Among four machine learning algorithms, XGBoost exhibited the best performance in combined models, achieving an AUC of 0.979 in the training set and 0.750 in the testing set, demonstrating its strong prognostic prediction capability. Conclusion: The superior performance of the XGBoost-based combined model underscores its potential as a powerful tool for enhancing the precision of prognostic assessments for patients with HCC.

Efficient retinal ganglion cells transduction by retro-orbital venous sinus injection of AAV-PHP.eB in mature mice.

Gene therapy is one of the strategies that may reduce or reverse progressive neurodegeneration in retinal neurodegenerative diseases. However, efficiently delivering transgenes to retinal ganglion cells (RGCs) remains hard to achieve. In this study, we innovatively investigated transduction efficiency of adeno-associated virus (AAV)-PHP.eB in murine RGCs by retro-orbital venous sinus injection. Five doses of AAV-PHP.eB-EGFP were retro-orbitally injected in venous sinus in adult C57/BL6J mice. Two weeks after administration, RGCs transduction efficiency was quantified by retinal flat-mounts and frozen section co-labeling with RGCs marker Rbpms. In addition, safety of this method was evaluated by RGCs survival rate and retinal morphology. To conform efficacy of this new method, AAV-PHP.eB-CNTF was administrated into mature mice through single retro-orbital venous injection after optic nerve crush injury to evaluate axonal elongation. Results indicated that AAV- PHP.eB readily crossed the blood-retina barrier and was able to transduce more than 90% of RGCs when total dose of virus reached 5 × 1010 vector genomes (vg). Moreover, this technique did not affect RGCs survival rate and retinal morphology. Furthermore, retro-orbital venous delivery of AAV-PHP.eB-CNTF effectively transduced RGCs, robustly promoted axonal regeneration after optic nerve crush injury. Thus, novel AAV-PHP.eB retro-orbital injection provides a minimally invasive and efficient route for transgene delivery in treatment of retinal neurodegenerative diseases.

Establishment of an Efficient Protoplast Isolation and Transfection Method for Eucommia ulmoides Oliver.

BACKGROUND: Eucommia ulmoides Oliver is a unique high-quality natural rubber tree species and rare medicinal tree species in China. The rapid characterization of E. ulmoides gene function has been severely hampered by the limitations of genetic transformation methods and breeding cycles. The polyethylene glycol (PEG)-mediated protoplast transformation system is a multifunctional and rapid tool for the analysis of functional genes in vivo, but it has not been established in E. ulmoides. METHODS: In this study, a large number of highly active protoplasts were isolated from the stems of E. ulmoides seedlings by enzymatic digestion, and green fluorescent protein expression was facilitated using a PEG-mediated method. RESULTS: Optimal enzymatic digestion occurred when the enzyme was digested for 10 h in an enzymatic solution containing 2.5% Cellulase R-10 (w/v), 0.6% Macerozyme R-10 (w/v), 2.5% pectinase (w/v), 0.5% hemicellulase (w/v), and 0.6 mol/L mannitol. The active protoplast yield under this condition was 1.13 × 106 protoplasts/g fresh weight, and the protoplast activity was as high as 94.84%. CONCLUSIONS: This study established the first protoplasm isolation and transient transformation system in hard rubber wood, which lays the foundation for subsequent functional studies of E. ulmoides genes to achieve high-throughput analysis, and provides a reference for future gene function studies of medicinal and woody plants.

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Trigeminal neuralgia is a manifestation of orofacial neuropathic pain disorder, always deemed to be an insurmountable peak in the field of pain research and treatment. The pain is recurrent, abrupt in onset and termination similar to an electric shock or described as shooting. A poor quality of life has been attributed to trigeminal neuralgia, as the paroxysms of pain may be triggered by innocuous stimuli on the face or inside the oral cavity, such as talking, washing face, chewing and brushing teeth in daily life. The pathogenesis of trigeminal neuralgia has not been fully elucidated, although the microvascular compression in the trigeminal root entry zone is generally considered to be involved in the emergence and progression of the pain disorder. In addition, orofacial neuropathic pain restricted to one or more divisions of the trigeminal nerve might be secondary to peripheral nerve injury. Based on current hypotheses regarding the potential causes, a variety of animal models have been designed to simulate the pathogenesis of trigeminal neuralgia, including models of compression applied to the trigeminal nerve root or trigeminal ganglion, chronic peripheral nerve injury, peripheral inflammatory pain and center-induced pain. However, it has not yet been possible to determine which model can be perfectly employed to explain the mechanisms. The selection of appropriate animal models is of great significance for the study of trigeminal neuralgia. Therefore, it is necessary to discuss the characteristics of the animal models in terms of animal strains, materials, operation methods and behavior observation, in order to gain insight into the research progress in animal models of trigeminal neuralgia. In the future, animal models that closely resemble the features of human trigeminal neuralgia pathogenesis need to be developed, with the aim of making valuable contributions to the relevant basic and translational medical research.

USP5 promotes tumorigenesis by activating Hedgehog/Gli1 signaling pathway in osteosarcoma.

Changes in protein ubiquitination have been linked to cancer. Deubiquitinating enzymes (DUBs) counteract E3 ligase activities and have emerged as promising targets for cancer treatment. Ubiquitin-specific peptidase 5 (USP5) is a member of the DUBs family and has been implicated in promoting tumorigenesis in numerous cancers. However, the clinical significance and biological function of USP5 in osteosarcoma (OS) remains unclear. Here, we found elevated USP5 expression in OS tissues compared with normal bone tissues. Furthermore, we observed significant associations of elevated USP5 levels with increased mortality and more malignant phenotypes in OS patients. Moreover, our results revealed that USP5 could facilitate metastasis and cell progression in OS by activating the hedgehog (Hh) signaling pathway using cultured cells and animal tumor models. Mechanistically, USP5 appeared to stabilize and deubiquitinate Gli1, a key mediator of the Hh signaling pathway. Additionally, the oncogenic effect of USP5 in OS was dependent on Gli1 stability. Our findings support the model where USP5 contributes to OS pathogenesis by activating the Hh/Gli1 signaling pathway, making USP5 a potential diagnostic and therapeutic target for OS.

Deep Reinforcement Learning-Based Energy Consumption Optimization for Peer-to-Peer (P2P) Communication in Wireless Sensor Networks.

The fast development of the sensors in the wireless sensor networks (WSN) brings a big challenge of low energy consumption requirements, and Peer-to-peer (P2P) communication becomes the important way to break this bottleneck. However, the interference caused by different sensors sharing the spectrum and the power limitations seriously constrains the improvement of WSN. Therefore, in this paper, we proposed a deep reinforcement learning-based energy consumption optimization for P2P communication in WSN. Specifically, P2P sensors (PUs) are considered agents to share the spectrum of authorized sensors (AUs). An authorized sensor has permission to access specific data or systems, while a P2P sensor directly communicates with other sensors without needing a central server. One involves permission, the other is direct communication between sensors. Each agent can control the power and select the resources to avoid interference. Moreover, we use a double deep Q network (DDQN) algorithm to help the agent learn more detailed features of the interference. Simulation results show that the proposed algorithm can obtain a higher performance than the deep Q network scheme and the traditional algorithm, which can effectively lower the energy consumption for P2P communication in WSN.

Genetic evidence strengthens the bidirectional connection between gut microbiota and Shigella infection: insights from a two-sample Mendelian randomization study.

Background: In recent investigations, substantial strides have been made in the precise modulation of the gut microbiota to prevent and treat a myriad of diseases. Simultaneously, the pressing issue of widespread antibiotic resistance and multidrug resistance resulting from Shigella infections demands urgent attention. Several studies suggest that the antagonistic influence of the gut microbiota could serve as a novel avenue for impeding the colonization of pathogenic microorganisms or treating Shigella infections. However, conventional research methodologies encounter inherent challenges in identifying antagonistic microbial agents against Shigella, necessitating a comprehensive and in-depth analysis of the causal relationship between Shigella infections and the gut microbiota. Materials and methods: Utilizing the aggregated summary statistics from Genome-Wide Association Studies (GWAS), we conducted Mendelian Randomization (MR) analyses encompassing 18,340 participants to explore the interplay between the gut microbiota and Shigella infections. This investigation also involved 83 cases of Shigella infection patients and 336,396 control subjects. In the positive strand of our findings, we initially performed a preliminary analysis using the Inverse Variance Weighting (IVW) method. Subsequently, we undertook sensitivity analyses to assess the robustness of the results, addressing confounding factors' influence. This involved employing the Leave-One-Out method and scrutinizing funnel plots to ensure the reliability of the MR analysis outcomes. Conclusively, a reverse MR analysis was carried out, employing the Wald ratio method due to the exposure of individual Single Nucleotide Polymorphisms (SNPs). This was undertaken to explore the plausible associations between Shigella infections and genetically predicted compositions of the gut microbiota. Results: In this study, we employed 2,818 SNPs associated with 211 species of gut microbiota as instrumental variables (IVs). Through IVW analysis, our positive MR findings revealed a significant negative correlation between the occurrence of Shigella infections and the phylum Tenericutes (OR: 0.18, 95% CI: 0.04-0.74, p = 0.02), class Mollicutes (OR: 0.18, 95% CI: 0.04-0.74, p = 0.02), genus Intestinimonas (OR: 0.16, 95% CI: 0.04-0.63, p = 0.01), genus Gordonibacter (OR: 0.39, 95% CI: 0.16-0.93, p = 0.03), and genus Butyrivibrio (OR: 0.44, 95% CI: 0.23-0.87, p = 0.02). Conversely, a positive correlation was observed between the occurrence of Shigella infections and genus Sutterella (OR: 10.16, 95% CI: 1.87-55.13, p = 0.01) and genus Alistipes (OR: 12.24, 95% CI: 1.71-87.34, p = 0.01). In sensitivity analyses, utilizing MR-Egger regression analysis and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) detection, all outcomes demonstrated robust stability. Simultaneously, in the reverse MR analysis, Shigella infections resulted in an upregulation of four bacterial genera and a downregulation of three bacterial genera. Conclusion: In summation, the MR analysis outcomes corroborate the presence of bidirectional causal relationships between the gut microbiota and Shigella infections. This study not only unveils novel perspectives for the prevention and treatment of Shigella infections but also furnishes fresh insights into the mechanistic underpinnings of how the gut microbiota contributes to the pathogenesis of Shigella infections. Consequently, the established dual causal association holds promise for advancing our understanding and addressing the complexities inherent in the interplay between the gut microbiota and Shigella infections, thereby paving the way for innovative therapeutic interventions and preventive strategies in the realm of Shigella-related diseases.

The complete chloroplast genome of Sinosenecio globigerus (C. C. Chang) B. Nordenstam (Asteraceae).

The genus Sinosenecio B. Nordenstam is a group of perennial or sometimes annual or biennial herbs in the family Asteraceae. Here, we have successfully assembled and characterized the complete chloroplast (cp) genome of S. globigerus, which shows a typical quadratic structure with an overall GC content of 37.4%, comprising a pair of inverted repeat regions (IRs) of 24,848 bp, a large single-copy region (LSC) of 83,379 bp and a small single-copy region (SSC) of 18,180 bp. 133 genes were annotated, including 88 protein-coding genes, 37 tRNA genes and eight rRNA genes. Further nucleotide diversity analysis indicated that three genomic regions (accD-psaI, trnK-rps16, and ycf1) exhibited sufficient variability and thus could be recommended as valuable barcodes for the delimitation and identification of Sinosenecio species. Phylogenetic reconstruction presented clear interspecific relationships within Sinosenecio, which were supported to some extent by cytology, morphology and geographic distributions. Our study will provide valuable and high-quality genetic information to further elucidate the diversified mechanisms in Sinosenecio.

Comparison of retinal parameters between rhesus and cynomolgus macaques.

Nonhuman primates are important research models for basic vision research, preclinical pathogenesis, and treatment studies due to strong similarities in retinal structure and function with humans. We compared retinal parameters between 10 healthy normal rhesus macaques (Macaca mulatta) and 10 cynomolgus macaques (Macaca fascicularis) by optical coherence tomography and electroretinography. The Heidelberg Spectralis® HRA+OCT and Roland multifocal electrophysiometer were used to analyze retinal morphology, multifocal electroretinograms (mfERGs), and full-field electroretinograms (ff-ERGs). Mean retinal thickness was lowest in the central fovea of macaques and did not differ significantly between species, but the retinal thicknesses of the nerve fiber ganglion cell layer and the inner plexiform layer were significantly different. The amplitude density of the N1 wave was lower in rhesus macaques than in cynomolgus macaques in ring and quadrant areas. Dark-adapted 3.0 oscillatory potentials (reflection of amacrine cell activity) and light-adapted 30-hz flicker ERG (a sensitive cone-pathway-driven response) waveforms of the ff-ERG were similar in both species, while the times to peaks in dark-adapted 0.01 ERG (the rod-driven response of bipolar cells) and dark-adapted 3.0 ERG (combined rod and cone system responses) as well as the implicit times of the a- and b-waves in light-adapted 3.0 ERG (the single-flash cone response) were substantially different. This study provides normative retinal parameters for nonhuman primate research on basic and clinical ophthalmology, as well as a reference for researchers in the appropriate selection of rhesus or cynomolgus macaques as models for ophthalmology studies.

A high mass loading flexible electrode with a sheet-like Mn3O4/NiMoO4@NiCo LDH on a carbon cloth for supercapacitors.

Mass loading is an important parameter to evaluate the application potential of active materials in high-capacity supercapacitors. Synthesizing active materials with high mass loading is a promising strategy to improve high performance energy storage devices. Preparing electrode materials with a porous structure is of significance to overcome the disadvantages brought by high mass loading. In this work, a Mn3O4/NiMoO4@NiCo layered double hydroxide (MO/NMO/NiCo LDH) positive electrode is fabricated on a carbon cloth with a high mass loading of 20.4 mg cm-2. The MO/NMO/NiCo LDH presents as a special three-dimensional porous nanostructure and exhibits a high specific capacitance of 815 F g-1 at 1 A g-1. Impressively, the flexible supercapacitor based on the MO/NMO/NiCo LDH positive electrode and an AC negative electrode delivers a maximum energy density of 22.5 W h kg-1 and a power density of 8730 W kg-1. It also retains 60.84% of the original specific capacitance after bending to 180° 600 times. Moreover, it exhibits 76.92% capacitance retention after 15 000 charge/discharge cycles. These results make MO/NMO/NiCo LDH one of the most attractive candidates of positive electrode materials for high-performance flexible supercapacitors.

Taxifolin Inhibits the Growth of Non-Small-Cell Lung Cancer via Downregulating Genes Displaying Novel and Robust Associations with Immune Evasion Factors.

Using an LL2 cell-based syngeneic mouse LC model, taxifolin suppressed allografts along with the appearance of 578 differentially expressed genes (DEGs). These DEGs were associated with enhancement of processes related to the extracellular matrix and lymphocyte chemotaxis as well as the reduction in pathways relevant to cell proliferation. From these DEGs, we formulated 12-gene (TxflSig) and 7-gene (TxflSig1) panels; both predicted response to ICB (immune checkpoint blockade) therapy more effectively in non-small-cell lung cancer (NSCLC) than numerous well-established ICB biomarkers, including PD-L1. In both panels, the mouse counterparts of ITGAL, ITGAX, and TMEM119 genes were downregulated by taxifolin. They were strongly associated with immune suppression in LC, evidenced by their robust correlations with the major immunosuppressive cell types (MDSC, Treg, and macrophage) and multiple immune checkpoints in NSCLC and across multiple human cancer types. ITGAL, ITGAX, and IIT (ITGAL-ITGAX-TMEM119) effectively predicted NSCLC's response to ICB therapy; IIT stratified the mortality risk of NSCLC. The stromal expressions of ITGAL and ITGAX, together with tumor expression of TMEM119 in NSCLC, were demonstrated. Collectively, we report multiple novel ICB biomarkers-TxflSig, TxflSig1, IIT, ITGAL, and ITGAX-and taxifolin-derived attenuation of immunosuppressive activities in NSCLC, suggesting the inclusion of taxifolin in ICB therapies for NSCLC.

Fully Integrated Microfluidic Device for Magnetic Bead Manipulation to Assist Rapid Reaction and Cleaning.

Methods to manipulate magnetic beads are essential factors to determine the efficiency and dimension of an in vitro diagnostic system. Currently, using movable permanent magnets and planar electromagnets is still the major approach to achieve magnetic bead control, causing significant constraint in the miniaturization of in vitro diagnostic systems. Here, we propose techniques to construct a fully integrated microfluidic device that can conduct automatic magnetic bead manipulation as well as rapid chemical reaction and cleaning in a minimized dimension similar to a USB disk. The device combines the precision control of multiple electromagnetic coils with the compactness of microfluidic channels, leading to one of the smallest automatic magnetic bead manipulation systems that can complete several major magnetic bead-based operation steps such as sample injection, reaction, cleaning, and collection. The influencing factors such as coil driving parameters, surface treatment of the microchannels, and properties of magnetic particles have also been investigated to optimize the device performance. The device can drive mixtures of Fe3O4 microparticles and polymer magnetic beads (PMBs) with a weight ratio of 1:1 at a maximum speed of 0.5 cm·s-1 and reduce the time for DNA binding and dissociation reactions from 20 min to only 48 s. This device has significantly advanced the conventional manipulation methods of magnetic beads and has demonstrated the possibility to construct an automatic and ultraminiaturized in vitro diagnostic system that may facilitate portable or even wearable chemical analysis.

Taxifolin Inhibits Breast Cancer Growth by Facilitating CD8+ T Cell Infiltration and Inducing a Novel Set of Genes including Potential Tumor Suppressor Genes in 1q21.3.

Taxifolin inhibits breast cancer (BC) via novel mechanisms. In a syngeneic mouse BC model, taxifolin suppressed 4T-1 cell-derived allografts. RNA-seq of 4T-1 tumors identified 36 differentially expressed genes (DEGs) upregulated by taxifolin. Among their human homologues, 19, 7, and 2 genes were downregulated in BCs, high-proliferative BCs, and BCs with high-fatality risks, respectively. Three genes were established as tumor suppressors and eight were novel to BC, including HNRN, KPRP, CRCT1, and FLG2. These four genes exhibit tumor suppressive actions and reside in 1q21.3, a locus amplified in 70% recurrent BCs, revealing a unique vulnerability of primary and recurrent BCs with 1q21.3 amplification with respect to taxifolin. Furthermore, the 36 DEGs formed a multiple gene panel (DEG36) that effectively stratified the fatality risk in luminal, HER2+, and triple-negative (TN) equivalent BCs in two large cohorts: the METABRIC and TCGA datasets. 4T-1 cells model human TNBC cells. The DEG36 most robustly predicted the poor prognosis of TNBCs and associated it with the infiltration of CD8+ T, NK, macrophages, and Th2 cells. Of note, taxifolin increased the CD8+ T cell content in 4T-1 tumors. The DEG36 is a novel and effective prognostic biomarker of BCs, particularly TNBCs, and can be used to assess the BC-associated immunosuppressive microenvironment.

Early pheromone perception remodels neurodevelopment and accelerates neurodegeneration in adult C. elegans.

Age-associated neurodegenerative disorders such as Parkinson's and Alzheimer's diseases are mainly caused by protein aggregation. The etiologies of these neurodegenerative diseases share a chemical environment. However, how chemical cues modulate neurodegeneration remains unclear. Here, we found that in Caenorhabditis elegans, exposure to pheromones in the L1 stage accelerates neurodegeneration in adults. Perception of pheromones ascr#3 and ascr#10 is mediated by chemosensory neurons ASK and ASI. ascr#3 perceived by G protein-coupled receptor (GPCR) DAF-38 in ASK activates glutamatergic transmission into AIA interneurons. ascr#10 perceived by GPCR STR-2 in ASI activates the secretion of neuropeptide NLP-1, which binds to the NPR-11 receptor in AIA. Activation of both ASI and ASK is required and sufficient to remodel neurodevelopment via AIA, which triggers insulin-like signaling and inhibits autophagy in adult neurons non-cell-autonomously. Our work reveals how pheromone perception at the early developmental stage modulates neurodegeneration in adults and provides insights into how the external environment impacts neurodegenerative diseases.

Use of random forest based on the effects of urban governance elements to forecast CO2 emissions in Chinese cities.

Chinese cities contributes a large amount of CO2 emissions. Reducing CO2 emissions through urban governance is an important issue. Despite the increasing attention paid on the CO2 emission prediction, few studies consider the collective and complex influence of governance element system. To predict and regulate CO2 emissions through comprehensive urban governance elements, this paper use the random forest model through the data from 1903 Chinese county-level cities in 2010, 2012 and 2015, and establish a CO2 forecasting platform based on the effects of urban governance elements. The results are as follows: (1) The municipal utility facilities element, the economic development & industrial structure element, and the city size &structure and road traffic facilities elements are crucial for residential, industrial and transportation CO2 emissions, respectively; (2) Governance elements have nonlinear relationship with CO2 emissions and most of the relations present obvious threshold effects; (3) Random forest can be used to predict CO2 emissions more accurately than can other predictive models. These findings can be used to conducts the CO2 scenario simulation and help government formulate active governance measurements.

Piperlongumine conquers temozolomide chemoradiotherapy resistance to achieve immune cure in refractory glioblastoma via boosting oxidative stress-inflamation-CD8+-T cell immunity.

BACKGROUND: The failure of novel therapies effective in preclinical animal models largely reflects the fact that current models do not really mimic the pathological/therapeutic features of glioblastoma (GBM), in which the most effective temozolomide chemoradiotherapy (RT/TMZ) regimen can only slightly extend survival. How to improve RT/TMZ efficacy remains a major challenge in clinic. METHODS: Syngeneic G422TN-GBM model mice were subject to RT/TMZ, surgery, piperlongumine (PL), αPD1, glutathione. Metabolomics or transcriptomics data from G422TN-GBM and human GBM were used for gene enrichment analysis and estimation of ROS generation/scavenging balance, oxidative stress damage, inflammation and immune cell infiltration. Overall survival, bioluminescent imaging, immunohistochemistry, and immunofluorescence staining were used to examine therapeutic efficacy and mechanisms of action. RESULTS: Here we identified that glutathione metabolism was most significantly altered in metabolomics analysis upon RT/TMZ therapies in a truly refractory and reliable mouse triple-negative GBM (G422TN) preclinical model. Consistently, ROS generators/scavengers were highly dysregulated in both G422TN-tumor and human GBM. The ROS-inducer PL synergized surgery/TMZ, surgery/RT/TMZ or RT/TMZ to achieve long-term survival (LTS) in G422TN-mice, but only one LTS-mouse from RT/TMZ/PL therapy passed the rechallenging phase (immune cure). Furthermore, the immunotherapy of RT/TMZ/PL plus anti-PD-1 antibody (αPD1) doubled LTS (50%) and immune-cured (25%) mice. Glutathione completely abolished PL-synergistic effects. Mechanistically, ROS reduction was associated with RT/TMZ-resistance. PL restored ROS level (mainly via reversing Duox2/Gpx2), activated oxidative stress/inflammation/immune responses signature genes, reduced cancer cell proliferation/invasion, increased apoptosis and CD3+/CD4+/CD8+ T-lymphocytes in G422TN-tumor on the basis of RT/TMZ regimen. CONCLUSION: Our findings demonstrate that PL reverses RT/TMZ-reduced ROS and synergistically resets tumor microenvironment to cure GBM. RT/TMZ/PL or RT/TMZ/PL/αPD1 exacts effective immune cure in refractory GBM, deserving a priority for clinical trials.