A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.

We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs, and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.

PALI1 promotes tumor growth through competitive recruitment of PRC2 to G9A-target chromatin for dual epigenetic silencing.

PALI1 is a newly identified accessory protein of the Polycomb repressive complex 2 (PRC2) that catalyzes H3K27 methylation. However, the roles of PALI1 in cancer are yet to be defined. Here, we report that PALI1 is upregulated in advanced prostate cancer (PCa) and competes with JARID2 for binding to the PRC2 core subunit SUZ12. PALI1 further interacts with the H3K9 methyltransferase G9A, bridging the formation of a unique G9A-PALI1-PRC2 super-complex that occupies a subset of G9A-target genes to mediate dual H3K9/K27 methylation and gene repression. Many of these genes are developmental regulators required for cell differentiation, and their loss in PCa predicts poor prognosis. Accordingly, PALI1 and G9A drive PCa cell proliferation and invasion in vitro and xenograft tumor growth in vivo. Collectively, our study shows that PALI1 harnesses two central epigenetic mechanisms to suppress cellular differentiation and promote tumorigenesis, which can be targeted by dual EZH2 and G9A inhibition.

Multimodal convergence in the pedunculopontine tegmental nucleus: Motor, sensory and theta-frequency inputs influence activity of single neurons.

The pedunculopontine tegmental nucleus of the brainstem (PPTg) has extensive interconnections and neuronal-behavioural correlates. It is implicated in movement control and sensorimotor integration. We investigated whether single neuron activity in freely moving rats is correlated with components of skilled forelimb movement, and whether individual neurons respond to both motor and sensory events. We found that individual PPTg neurons showed changes in firing rate at different times during the reach. This type of temporally specific modulation is like activity seen elsewhere in voluntary movement control circuits, such as the motor cortex, and suggests that PPTg neural activity is related to different specific events occurring during the reach. In particular, many neuronal modulations were time-locked to the end of the extension phase of the reach, when fine distal movements related to food grasping occur, indicating strong engagement of PPTg in this phase of skilled individual forelimb movements. In addition, some neurons showed brief periods of apparent oscillatory firing in the theta range at specific phases of the reach-to-grasp movement. When movement-related neurons were tested with tone stimuli, many also responded to this auditory input, allowing for sensorimotor integration at the cellular level. Together, these data extend the concept of the PPTg as an integrative structure in generation of complex movements, by showing that this function extends to the highly coordinated control of the forelimb during skilled reach to grasp movement, and that sensory and motor-related information converges on single neurons, allowing for direct integration at the cellular level.

Mapping Knowledge Landscapes and Emerging Trends in AI for Dementia Biomarkers: Bibliometric and Visualization Analysis.

BACKGROUND: With the rise of artificial intelligence (AI) in the field of dementia biomarker research, exploring its current developmental trends and research focuses has become increasingly important. This study, using literature data mining, analyzes and assesses the key contributions and development scale of AI in dementia biomarker research. OBJECTIVE: The aim of this study was to comprehensively evaluate the current state, hot topics, and future trends of AI in dementia biomarker research globally. METHODS: This study thoroughly analyzed the literature in the application of AI to dementia biomarkers across various dimensions, such as publication volume, authors, institutions, journals, and countries, based on the Web of Science Core Collection. In addition, scales, trends, and potential connections between AI and biomarkers were extracted and deeply analyzed through multiple expert panels. RESULTS: To date, the field includes 1070 publications across 362 journals, involving 74 countries and 1793 major research institutions, with a total of 6455 researchers. Notably, 69.41% (994/1432) of the researchers ceased their studies before 2019. The most prevalent algorithms used are support vector machines, random forests, and neural networks. Current research frequently focuses on biomarkers such as imaging biomarkers, cerebrospinal fluid biomarkers, genetic biomarkers, and blood biomarkers. Recent advances have highlighted significant discoveries in biomarkers related to imaging, genetics, and blood, with growth in studies on digital and ophthalmic biomarkers. CONCLUSIONS: The field is currently in a phase of stable development, receiving widespread attention from numerous countries, institutions, and researchers worldwide. Despite this, stable clusters of collaborative research have yet to be established, and there is a pressing need to enhance interdisciplinary collaboration. Algorithm development has shown prominence, especially the application of support vector machines and neural networks in imaging studies. Looking forward, newly discovered biomarkers are expected to undergo further validation, and new types, such as digital biomarkers, will garner increased research interest and attention.

Effectiveness of High-Frequency Repetitive Transcranial Magnetic Stimulation in Patients With Spinocerebellar Ataxia Type 3.

OBJECTIVE: To investigate the effectiveness of high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) on improvement of clinical symptoms in patients with spinocerebellar ataxia type 3 (SCA3). METHODS: Sixteen SCA3 participants diagnosed by genetic testing were enrolled in this sham-controlled and double-blind trial. They received either a 2-week 10-Hz rTMS intervention or sham stimulation targeting the vermis and cerebellum. The Scale for Assessment and Rating of Ataxia and the International Cooperative Ataxia Rating Scale were completed at baseline and poststimulation. RESULTS: Compared with baseline, the HF-rTMS group demonstrated a significant improvement in the total Scale for Assessment and Rating of Ataxia ( P < 0.0001) and the International Cooperative Ataxia Rating Scale scores ( P = 0.002). After 2-week treatment, the real group exhibited decreasing pattern in 3 subgroups, especially for limb kinetic function ( P < 0.0001). CONCLUSIONS: Short-term HF-rTMS treatment is a potentially promising and feasible tool for rehabilitation in patients with SCA3. Studies with long-term follow-up need to be carried out in the future and further need to assess gait, limb kinetic function, speech and oculomotor disorders.

Improving deconvolution methods in biology through open innovation competitions: an application to the connectivity map.

MOTIVATION: Do machine learning methods improve standard deconvolution techniques for gene expression data? This article uses a unique new dataset combined with an open innovation competition to evaluate a wide range of approaches developed by 294 competitors from 20 countries. The competition's objective was to address a deconvolution problem critical to analyzing genetic perturbations from the Connectivity Map. The issue consists of separating gene expression of individual genes from raw measurements obtained from gene pairs. We evaluated the outcomes using ground-truth data (direct measurements for single genes) obtained from the same samples. RESULTS: We find that the top-ranked algorithm, based on random forest regression, beat the other methods in accuracy and reproducibility; more traditional gaussian-mixture methods performed well and tended to be faster, and the best deep learning approach yielded outcomes slightly inferior to the above methods. We anticipate researchers in the field will find the dataset and algorithms developed in this study to be a powerful research tool for benchmarking their deconvolution methods and a resource useful for multiple applications. AVAILABILITY AND IMPLEMENTATION: The data is freely available at clue.io/data (section Contests) and the software is on GitHub at https://github.com/cmap/gene_deconvolution_challenge. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pepsinogen C expression-related lncRNA/circRNA/mRNA profile and its co-mediated ceRNA network in gastric cancer.

The expression of pepsinogen C (PGC) is considered an ideal negative biomarker of gastric cancer, but its pathological mechanisms remain unclear. This study aims to analyze competing endogenous RNA (ceRNA) networks related to PGC expression at a post-transcriptional level and build an experimental basis for studying the role of PGC in the progression of gastric cancer. RNA sequencing technology was used to detect the differential expression (DE) profiles of PGC-related long non-coding (lnc)RNAs, circular (circ)RNAs, and mRNAs. Ggcorrplot R package and online database were used to construct DElncRNAs/DEcircRNAs co-mediated PGC expression-related ceRNA networks. In vivo and in vitro validations were performed using quantitative reverse transcription-PCR (qRT-PCR). RNA sequencing found 637 DEmRNAs, 698 DElncRNAs, and 38 DEcircRNAs. The PPI network of PGC expression-related mRNAs consisted of 503 nodes and 1179 edges. CFH, PPARG, and MUC6 directly interacted with PGC. Enrichment analysis suggested that DEmRNAs were mainly enriched in cancer-related pathways. Eleven DElncRNAs, 13 circRNAs, and 35 miRNA-mRNA pairs were used to construct ceRNA networks co-mediated by DElncRNAs and DEcircRNAs that were PGC expression-related. The network directly related to PGC was as follows: SNHG16/hsa_circ_0008197-hsa-mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p-PGC. qRT-PCR validation results showed that PGC, PPARG, SNHG16, and hsa_circ_0008197 were differentially expressed in gastric cancer cells and tissues: PGC positively correlated with PPARG (r = 0.276, P = 0.009), SNHG16 (r = 0.35, P = 0.002), and hsa_circ_0008197 (r = 0.346, P = 0.005). PGC-related DElncRNAs and DEcircRNAs co-mediated complicated ceRNA networks to regulate PGC expression, thus affecting the occurrence and development of gastric cancer at a post-transcriptional level. Of these, the network directly associated with PGC expression was a SNHG16/hsa_circ_0008197-mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p - PGC axis. This study may form a foundation for the subsequent exploration of the possible regulatory mechanisms of PGC in gastric cancer.

XPF expression and its relationship with the risk and prognosis of colorectal cancer.

BACKGROUND: XPF (xeroderma pigmentosum complementation group F) is a key factor contributing to DNA damage excision of nucleotide excision repair pathway. The relationship between XPF expression and the risk and prognosis of colorectal cancer (CRC) is unclear. METHODS: In this experiment, a total of 824 cases of colorectal tissue were collected. XPF protein expression was detected by immunohistochemical staining. We conducted a Mann-Whitney U test in order to explore the differential expression of XPF between CRC and non-cancer controls, and the correlation between XPF expression and CRC clinicopathological parameters. Univariate and multivariate Cox regression analyses were conducted to investigate the relationship between XPF expression and CRC prognosis. The Java based software GSEA as well as STRING, David, GO, KEGG were used to explore the function and regulation network of XPF. RESULTS: The results demonstrated that the XPF expression in CRC was significantly up-regulated compared with non-tumor controls (P < 0.001) and adenoma tissue (P < 0.001). XPF protein was increased in the dynamic sequence of anal diseases to adenoma tissue to CRC. Expression of XPF was related to tumor location (P = 0.005) and tumor growth pattern (P = 0.009). The results of prognosis analysis suggested that in patients with stage T1-T2, XPF low expression may be significantly associated with better overall survival (HR = 7.978, 95% CI 1.208-52.673, P = 0.031). XPF and its interacting genes played a vital role in different processes of nucleotide excision repair pathway. XPF expression was related with Ubiquitin like protein specific protease activity. CONCLUSIONS: XPF might be a promising biomarker for CRC risk, and also showed potential as a prognostic predictor in CRC patients.

Comprehensive genomic characterization of NAC transcription factor family and their response to salt and drought stress in peanut.

BACKGROUND: Peanut is one of the most important oil crop species worldwide. NAC transcription factor (TF) genes play important roles in the salt and drought stress responses of plants by activating or repressing target gene expression. However, little is known about NAC genes in peanut. RESULTS: We performed a genome-wide characterization of NAC genes from the diploid wild peanut species Arachis duranensis and Arachis ipaensis, which included analyses of chromosomal locations, gene structures, conserved motifs, expression patterns, and cis-acting elements within their promoter regions. In total, 81 and 79 NAC genes were identified from A. duranensis and A. ipaensis genomes. Phylogenetic analysis of peanut NACs along with their Arabidopsis and rice counterparts categorized these proteins into 18 distinct subgroups. Fifty-one orthologous gene pairs were identified, and 46 orthologues were found to be highly syntenic on the chromosomes of both A. duranensis and A. ipaensis. Comparative RNA sequencing (RNA-seq)-based analysis revealed that the expression of 43 NAC genes was up- or downregulated under salt stress and under drought stress. Among these genes, the expression of 17 genes in cultivated peanut (Arachis hypogaea) was up- or downregulated under both stresses. Moreover, quantitative reverse transcription PCR (RT-qPCR)-based analysis revealed that the expression of most of the randomly selected NAC genes tended to be consistent with the comparative RNA-seq results. CONCLUSION: Our results facilitated the functional characterization of peanut NAC genes, and the genes involved in salt and drought stress responses identified in this study could be potential genes for peanut improvement.

Low Ca2+ concentration doping enhances the mechanical properties and ionic conductivity of Na3PS4 superionic conductors based on first-principles.

The mechanical strength and ionic conductivity of sulfide solid electrolytes have received widespread attention for their application in solid sodium batteries. Herein, first-principles calculations are used to determine the properties, including the electronic, mechanical and ionic transport properties, of Na3PS4 sulfide solid electrolytes doped with low and high Ca ion concentrations. Our theoretical results demonstrate that low Ca ion concentrations can be easily doped in tetragonal and cubic phases (t-Na3PS4 and c-Na3PS4) and create a suitable number of Na vacancies based on the formation energy analysis. Furthermore, the calculated density of states and charge density differences indicate that the surrounding electronic environment is changed, and Ca-S ionic bonds are formed in Na3PS4 with Ca-doping. In addition, the improved ductility and mechanical strength of c-Na3PS4 and t-Na3PS4 achieved by low-concentration Ca doping may help suppress dendritic growth and electrode deformation. Finally, sodium ion migration in Ca-doped Na3PS4 is described with the aid of the CI-NEB method, and it is found that the migration energy barriers are less than those of pure Na3PS4, which suggests that the sodium ion conductivity can be effectively improved by doping with low Ca2+ concentrations. The present work improves the understanding of the influence of doping on the performance of solid electrolytes and provides a feasible framework for the future design of high-performance solid electrodes.

Non-linear association of plasma level of high-density lipoprotein cholesterol with endobronchial biopsy bleeding in patients with lung cancer.

BACKGROUND: Despite a large body of studies have demonstrated the multifaceted behavior of high-density lipoproteins (HDLs) in several physiological and pathological processes, the levels of plasma HDL-cholesterol (HDL-C) that may be associated with endobronchial biopsy (EBB)-related bleeding have never been examined. METHODS: We conducted a single-center retrospective cohort study of 628 consecutive patients with primary lung cancer who had undergone EBB at a large tertiary hospital between January 2014 and February 2018. Patients were divided into the bleeding group and the non-bleeding group according to the bronchoscopy report. The association between HDL-C levels and EBB-induced bleeding was evaluated using the LASSO regression analysis, multiple regression analysis and smooth curve fitting adjusted for potential confounders. RESULTS: There was an inverse association of plasma HDL-C concentration with the incidence of EBB-induced bleeding as assessed by univariate analysis (P < 0.05). However, in piecewise linear regression analysis, a non-linear relationship with threshold saturation effects was observed between plasma HDL-C concentrations and EBB-induced bleeding. The incidence of EBB-induced bleeding decreased with HDL-C concentrations from 1.5 mmol/L up to 2.0 mmol/L (adjusted OR, 0.39; 95% CI, 0.20-0.74), but increased with HDL-C levels above the inflection point (HDL-C = 2.0 mmol/L). CONCLUSIONS: There was a non-linear association between plasma HDL-C concentrations and the risk of EBB-induced bleeding in patients with lung cancer. The plasma level of HDL-C above 2.0 mmol/L or below 1.5 mmol/L may increase the risk of EBB-induced bleeding.

Two-cavity light-trapping scheme used in ultrathin c-Si solar cells.

A new high-efficiency light-trapping structure (HE-LTS) with two cavities is proposed and designed for ultrathin c-Si solar cells. The results show that by optimizing the size parameters of the HE-LTS, the photocurrent density value of a c-Si solar cell with its active layer equal to 4.5 µm is close to that of Lambertian LTS at each wavelength in the range from 300 nm to 970 nm and greatly exceeds that of Lambertian LTS at each wavelength in the range from 970 nm to 1200 nm; the photocurrent density of the HE-LTS can exceed that of Lambertian LTS by adjusting the size parameters in a wide range.

Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes.

Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures.

Plasma apolipoprotein E level is associated with the risk of endobronchial biopsy-induced bleeding in patients with lung cancer.

BACKGROUND: Factors affecting the risk of bleeding by bronchoscopic biopsy in patients with lung cancer remain unclear. The levels of plasma apolipoprotein E (ApoE) that may be associated with endobronchial biopsy (EBB)-induced bleeding have never been examined. METHODS: This was a retrospective study using data collected from 615 consecutive patients who had undergone EBB and been diagnosed with primary lung cancer from January 2014 through February 2018. Patients were either classified as the bleeding group (n = 214) or the non-bleeding group (n = 391) based on the bronchoscopy report. Multiple regression analysis was done to estimate the independent relationship between ApoE levels and EBB-induced bleeding, with an adjustment for potential confounders. RESULTS: The mean plasma ApoE concentration was higher in the non-bleeding group compared to that in the bleeding group (P < 0.05). However, a non-linear relationship with threshold effects was observed between plasma ApoE levels and EBB-induced bleeding in a piecewise linear regression analysis. The risk of EBB-induced bleeding decreased with ApoE concentrations from 3.5 mg/dL up to 5.9 mg/dL (adjusted odds ratio, 0.64; 95% confidence interval, 0.43-0.94); however, the incidence of EBB-induced bleeding increased with ApoE levels above the turning point (ApoE = 5.9 mg/dL). CONCLUSIONS: There was a non-linear association between plasma ApoE levels and the risk of EBB-induced bleeding. Higher plasma ApoE concentrations (> 5.9 mg/dL) are the independent risk factor for hemorrhage during EBB in patients with lung cancer.

Multiple P-TEFbs cooperatively regulate the release of promoter-proximally paused RNA polymerase II.

The association of DSIF and NELF with initiated RNA Polymerase II (Pol II) is the general mechanism for inducing promoter-proximal pausing of Pol II. However, it remains largely unclear how the paused Pol II is released in response to stimulation. Here, we show that the release of the paused Pol II is cooperatively regulated by multiple P-TEFbs which are recruited by bromodomain-containing protein Brd4 and super elongation complex (SEC) via different recruitment mechanisms. Upon stimulation, Brd4 recruits P-TEFb to Spt5/DSIF via a recruitment pathway consisting of Med1, Med23 and Tat-SF1, whereas SEC recruits P-TEFb to NELF-A and NELF-E via Paf1c and Med26, respectively. P-TEFb-mediated phosphorylation of Spt5, NELF-A and NELF-E results in the dissociation of NELF from Pol II, thereby transiting transcription from pausing to elongation. Additionally, we demonstrate that P-TEFb-mediated Ser2 phosphorylation of Pol II is dispensable for pause release. Therefore, our studies reveal a co-regulatory mechanism of Brd4 and SEC in modulating the transcriptional pause release by recruiting multiple P-TEFbs via a Mediator- and Paf1c-coordinated recruitment network.

Multiplexed determination of intracellular messenger RNA by using a graphene oxide nanoprobe modified with target-recognizing fluorescent oligonucleotides.

A multiplexed graphene oxide (GO) fluorescent nanoprobe is described for quantification and imaging of messenger RNAs (mRNAs) in living cells. The recognizing oligonucleotides (with sequences complementary to those of target mRNAs) were labeled with different fluorescent dyes. If adsorbed on GO, the fluorescence of the recognizing oligonucleotides is quenched. After having penetrated living cells, the oligonucleotides bind to target mRNAs and dissociate from GO. This leads to the recovery of fluorescence. Using different fluorescent dyes, various intracellular mRNAs can be simultaneously imaged and quantified by a high content analysis within a short period of time. Actin mRNA acts as the internal control. This GO-based nanoprobe allows mRNA mimics to be determined within an analytical range from 1 to 400 nM and a detection limit as low as 0.26 nM. Up to 3 intracellular mRNAs (C-myc, TK1, and actin) can be detected simultaneously in a single living cell. Hence, this nanoprobe enables specific distinction of intracellular mRNA expression levels in cancerous and normal cells. It can be potentially applied as a tool for detection of cancer progression and diagnosis. Graphical abstract A multiplexed graphene oxide (GO)-based fluorescent nanoprobe is described for quantification and imaging of intracellular messenger RNAs. After penetrating living cells, the recovered fluorescence of the dissociated recognizing oligonucleotides can be analyzed , and this allows for simultaneous detection of up to 3 intracellular messenger RNAs.

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles.

Inspired by the problem that the current spatial registration methods are unsuitable for three-dimensional (3-D) sensor on high-dynamic platform, this paper focuses on the estimation for the registration errors of cooperative missiles and motion states of maneuvering target. There are two types of errors being discussed: sensor measurement biases and attitude biases. Firstly, an improved Kalman Filter on Earth-Centered Earth-Fixed (ECEF-KF) coordinate algorithm is proposed to estimate the deviations mentioned above, from which the outcomes are furtherly compensated to the error terms. Secondly, the Pseudo Linear Kalman Filter (PLKF) and the nonlinear scheme the Unscented Kalman Filter (UKF) with modified inputs are employed for target tracking. The convergence of filtering results are monitored by a position-judgement logic, and a low-pass first order filter is selectively introduced before compensation to inhibit the jitter of estimations. In the simulation, the ECEF-KF enhancement is proven to improve the accuracy and robustness of the space alignment, while the conditional-compensation-based PLKF method is demonstrated to be the optimal performance in target tracking.

Exposure to complex environments results in more sparse representations of space in the hippocampus.

The neural circuitry mediating sensory and motor representations is adaptively tuned by an animal's interaction with its environment. Similarly, higher order representations such as spatial memories can be modified by exposure to a complex environment (CE), but in this case the changes in brain circuitry that mediate the effect are less well understood. Here, we show that prolonged CE exposure was associated with increased selectivity of CA1 "place cells" to a particular recording arena compared to a social control (SC) group. Furthermore, fewer CA1 and DG neurons in the CE group expressed high levels of Arc protein, a marker of recent activation, following brief exposure to a completely novel environment. The reduced Arc expression was not attributable to overall changes in cell density or number. These data indicate that one effect of CE exposure is to modify high-level spatial representations in the brain by increasing the sparsity of population coding within networks of neurons. Greater sparsity could result in a more efficient and compact coding system that might alter behavioural performance on spatial tasks. The results from a behavioural experiment were consistent with this hypothesis, as CE-treated animals habituated more rapidly to a novel environment despite showing equivalent initial responding.