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Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this study, we develop a deep variational autoencoder (VAE) model to compress thousands of genes into latent vectors in a low-dimensional space. We then demonstrate that these encoded vectors could accurately impute drug response, outperform standard signature-gene based approaches, and appropriately control the overfitting problem. We apply rigorous quality assessment and validation, including assessing the impact of cell line lineage, cross-validation, cross-panel evaluation, and application in independent clinical data sets, to warrant the accuracy of the imputed drug response in both cell lines and cancer samples. Specifically, the expression-regulated component (EReX) of the observed drug response achieves high correlation across panels. Using the well-trained models, we impute drug response of The Cancer Genome Atlas data and investigate the features and signatures associated with the imputed drug response, including cell line origins, somatic mutations and tumor mutation burdens, tumor microenvironment, and confounding factors. In summary, our deep learning method and the results are useful for the study of signatures and markers of drug response. Drug response in cancer patients vary dramatically due to inter- and intra-tumor heterogeneity and transcriptome context plays a significant role in shaping the actual treatment outcome. Here, the authors develop a deep variational autoencoder model to compress gene signatures into latent vectors and accurately impute drug response.

Background Postoperative cognitive dysfunction (POCD) is a very common complication that might increase the morbidity and mortality of elderly patients after surgery. However, the mechanism of POCD remains largely unknown. The NAD-dependent deacetylase protein Sirtuin 3 (SIRT3) is located in the mitochondria and regulates mitochondrial function. SIRT3 is the only sirtuin that specifically plays a role in extending lifespan in humans and is associated with neurodegenerative diseases. Therefore, the aim of this study was to evaluate the effect of SIRT3 on anesthesia/surgery-induced cognitive impairment in aged mice. Methods SIRT3 expression levels were decreased after surgery. For the interventional study, an adeno-associated virus (AAV)-SIRT3 vector or an empty vector was microinjected into hippocampal CA1 region before anesthesia/surgery. Western blotting, immunofluorescence staining, and enzyme-linked immune-sorbent assay (ELISA) were used to measure the oxidative stress response and downstream microglial activation and proinflammatory cytokines, and Golgi staining and long-term potentiation (LTP) recording were applied to evaluate synaptic plasticity. Results Overexpression of SIRT3 in the CA1 region attenuated anesthesia/surgery-induced learning and memory dysfunction as well as synaptic plasticity dysfunction and the oxidative stress response (superoxide dismutase [SOD] and malondialdehyde [MDA]) in aged mice with POCD. In addition, microglia activation (ionized calcium binding adapter molecule 1 [Iba1]) and neuroinflammatory cytokine levels (tumor necrosis factor-alpha [TNF-α], interleukin [IL]-1β and IL-6) were regulated after anesthesia/surgery in a SIRT3-dependent manner. Conclusion The results of the current study demonstrate that SIRT3 has a critical effect in the mechanism of POCD in aged mice by suppressing hippocampal neuroinflammation and reveal that SIRT3 may be a promising therapeutic and diagnostic target for POCD.

Background Heart failure (HF) has been recognized as a global pandemic with a high rate of hospitalization, morbidity, and mortality. Although numerous advances have been made, its representative molecular signatures remain largely unknown, especially the role of genes in HF progression. The aim of the present prospective follow-up study was to reveal potential biomarkers associated with the progression of heart failure. Methods We generated multi-level transcriptomic data from a cohort of left ventricular heart tissue collected from 21 HF patients and 9 healthy donors. By using Masson staining to calculate the fibrosis percentage for each sample, we applied lasso regression model to identify the genes associated with fibrosis as well as progression. The genes were further validated by immunohistochemistry (IHC) staining in the same cohort and qRT-PCR using another independent cohort (20 HF and 9 healthy donors). Enzyme-linked immunosorbent assay (ELISA) was used to measure the plasma level in a validation cohort (139 HF patients) for predicting HF progression. Results Based on the multi-level transcriptomic data, we examined differentially expressed genes [mRNAs, microRNAs, and long non-coding RNAs (lncRNAs)] in the study cohort. The follow-up functional annotation and regulatory network analyses revealed their potential roles in regulating extracellular matrix. We further identified several genes that were associated with fibrosis. By using the survival time before transplantation, COL1A1 was identified as a potential biomarker for HF progression and its upregulation was confirmed by both IHC and qRT-PCR. Furthermore, COL1A1 content ≥ 256.5 ng/ml in plasma was found to be associated with poor survival within 1 year of heart transplantation from heart failure [hazard ratio (HR) 7.4, 95% confidence interval (CI) 3.5 to 15.8, Log-rank p value < 1.0 × 10 − 4 ]. Conclusions Our results suggested that COL1A1 might be a plasma biomarker of HF and associated with HF progression, especially to predict the 1-year survival from HF onset to transplantation.

The oxidized platinum (Pt) can exhibit better electrocatalytic activity than metallic Pt 0 in the hydrogen evolution reaction (HER), which has aroused great interest in exploring the role of oxygen in Pt-based catalysts. Herein, we select two structurally well-defined polyoxometalates Na 5 [H 3 Pt (IV) W 6 O 24 ] (PtW 6 O 24 ) and Na 3 K 5 [Pt (II) 2 (W 5 O 18 ) 2 ] (Pt 2 (W 5 O 18 ) 2 ) as the platinum oxide model to investigate the HER performance. Electrocatalytic experiments show the mass activities of PtW 6 O 24 /C and Pt 2 (W 5 O 18 ) 2 /C are 20.175 A mg −1 and 10.976 A mg −1 at 77 mV, respectively, which are better than that of commercial 20% Pt/C (0.398 A mg −1 ). The in situ synchrotron radiation experiments and DFT calculations suggest that the elongated Pt-O bond acts as the active site during the HER process, which can accelerate the coupling of proton and electron and the rapid release of H 2 . This work complements the knowledge boundary of Pt-based electrocatalytic HER, and suggests another way to update the state-of-the-art electrocatalyst. While converting water to H 2 with a catalyst offers a renewable means to produce carbon-neutral fuels, understanding the catalytic active sites has proven challenging. Here, authors show a structurally well-defined model complex with Pt-O bonding to enable efficient H 2 evolution electrocatalysis.

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

IL-17-producing CD8 + (Tc17) cells are enriched in active lesions of patients with multiple sclerosis (MS), suggesting a role in the pathogenesis of autoimmunity. Here we show that amelioration of MS by dimethyl fumarate (DMF), a mechanistically elusive drug, associates with suppression of Tc17 cells. DMF treatment results in reduced frequency of Tc17, contrary to Th17 cells, and in a decreased ratio of the regulators RORC -to- TBX21 , along with a shift towards cytotoxic T lymphocyte gene expression signature in CD8 + T cells from MS patients. Mechanistically, DMF potentiates the PI3K-AKT-FOXO1-T-BET pathway, thereby limiting IL-17 and RORγt expression as well as STAT5-signaling in a glutathione-dependent manner. This results in chromatin remodeling at the Il17 locus. Consequently, T-BET-deficiency in mice or inhibition of PI3K-AKT, STAT5 or reactive oxygen species prevents DMF-mediated Tc17 suppression. Overall, our data disclose a DMF-AKT-T-BET driven immune modulation and suggest putative therapy targets in MS and beyond. Dimethyl fumarate (DMF) is a therapy for multiple sclerosis (MS) with undetermined mechanism of action. Here the authors find that clinical response to DMF associates with decrease in IL-17-producing CD8 +  T cells (Tc17), delineate molecular pathways involved, and show that DMF suppresses Tc17 pathogenicity in a mouse model of MS.

Understanding the underlying molecular mechanisms of liver fibrosis is important to develop effective therapy. Herein, we show that focal-adhesion-kinse (FAK) plays a key role in promoting hepatic stellate cells (HSCs) activation in vitro and liver fibrosis progression in vivo . FAK activation is associated with increased expression of α-smooth muscle actin (α-SMA) and collagen in fibrotic live tissues. Transforming growth factor beta-1 (TGF-β1) induces FAK activation in a time and dose dependent manner. FAK activation precedes the α-SMA expression in HSCs. Inhibition of FAK activation blocks the α-SMA and collagen expression, and inhibits the formation of stress fibers in TGF-β1 treated HSCs. Furthermore, inhibition of FAK activation significantly reduces HSC migration and small GTPase activation, and induces apoptotic signaling in TGF-β1 treated HSCs. Importantly, FAK inhibitor attenuates liver fibrosis in vivo and significantly reduces collagen and α-SMA expression in an animal model of liver fibrosis. These data demonstrate that FAK plays an essential role in HSC activation and liver fibrosis progression, and FAK signaling pathway could be a potential target for liver fibrosis.

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

This study explores the spatiotemporal distribution characteristics of ecosystem services (ESs) in the karst region of southeastern Yunnan under the backdrop of climate change. The study innovatively calculates the sustainable development goals (SDG) index based on ecosystem services (ESs). It employs the patch-generating land use simulation (PLUS) model to simulate future land use changes (LUCs) and uses the integrated valuation of ecosystem services and tradeoffs (InVEST) model to assess ESs under different scenarios. This research systematically evaluates the ESs and SDGs in karst regions within the context of climate change. The results indicate that: (1) Under all three scenarios in 2035, the trend of LUCs in the karst area of southeastern Yunnan is highly consistent, though the intensity and spatial configuration vary significantly. The least reduction in arable land area occurs under the shared socioeconomic pathways (SSP) 126 scenario, while water bodies and construction land show varying degrees of increase; (2) Regarding ESs, both water yield and soil retention exhibit an increasing trend across all scenarios by 2035, with the most notable rise under SSP126. Conversely, habitat quality and carbon storage show a decline, with the smallest decrease also under SSP126; (3) Analyzing the SDG index, the overall value is low in 2020. In future scenarios, the SDG index increases in the southern part while decreasing in the eastern part, indicating significant differences in regional sustainable development potential. Hotspots under SSP126 and SSP245 are concentrated in the densely vegetated southwest and eastern edge areas, while cold spots are mainly found in the heavily human-impacted central Yunnan urban agglomeration and Wenshan City. This study systematically explores for the first time the spatiotemporal dynamics of ESs in the karst region of southeastern Yunnan under different climate scenarios. It provides scientific evidence for regional ecological protection and land use planning.

: Circular RNAs (circRNAs) are a new form of noncoding RNAs that play crucial roles in various pathological processes. However, the expression profile and function of circRNAs in hepatic fibrosis (HF) remain largely unknown. In this study, we show a novel circFBXW4 mediates HF via targeting the miR-18b-3p/FBXW7 axis. : We investigated the expression profile of circRNAs, microRNAs and mRNAs in hepatic stellate cells (HSCs) from HF progression and regression mice by circRNAs-seq and microarray analysis. We found a significantly dysregulated circFBXW4 in HF. Loss-of-function and gain-of-function analysis of circFBXW4 were performed to assess the role of circFBXW4 in HF. Furthermore, we confirmed that circFBXW4 directly binds to miR-18b-3p by luciferase reporter assay, RNA pull down and fluorescence in situ hybridization analysis. : We found that circFBXW4 downregulated in liver fibrogenesis. Enforcing the expression of circFBXW4 inhibited HSCs activation, proliferation and induced apoptosis, attenuated mouse liver fibrogenesis injury and showed anti-inflammation effect. Mechanistically, circFBXW4 directly targeted to miR-18b-3p to regulate the expression of FBXW7 in HF. : circFBXW4 may act as a suppressor of HSCs activation and HF through the circFBXW4/miR-18b-3p/FBXW7 axis. Our findings identify that circFBXW4 serves as a potential biomarker for HF therapy.