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Screening for early‐stage disease is vital for reducing colorectal cancer (CRC)‐related mortality. Methylation of circulating tumor DNA has been previously used for various types of cancer screening. A novel cell‐free DNA (cfDNA) methylation‐based model which can improve the early detection of CRC is warranted. For our study, we collected 313 tissue and 577 plasma samples from patients with CRC, advanced adenoma (AA), non‐AA and healthy controls. After quality control, 187 tissue DNA samples (91 non‐malignant tissue from CRC patients, 26 AA and 70 CRC) and 489 plasma cfDNA samples were selected for targeted DNA methylation sequencing. We further developed a cfDNA methylation model based on 11 methylation biomarkers for CRC detection in the training cohort (area under curve [AUC] = 0.90 (0.85–0.94]) and verified the model in the validation cohort (AUC = 0.92 [0.88–0.96]). The cfDNA methylation model robustly detected patients pre‐diagnosed with early‐stage CRC (AUC = 0.90 [0.86–0.95]) or AA (AUC = 0.85 [0.78–0.91]). Here we established and validated a non‐invasive cfDNA methylation model based on 11 DNA methylation biomarkers for the detection of early‐stage CRC and AA. The utilization of the model in clinical practice may contribute to the early diagnosis of CRC. Cell‐free DNA (cfDNA) methylation is promising for colorectal cancer (CRC) screening. In this study, after DNA methylation sequencing of tissue and plasma samples, we established a cfDNA methylation model based on 11 DNA methylation biomarkers for the detection of early‐stage CRC and advanced adenoma. The utilization of the model may contribute to the non‐invasive early diagnosis of CRC.

The human brain has enormously complex cellular diversity and connectivities fundamental to our neural functions, yet difficulties in interrogating individual neurons has impeded understanding of the underlying transcriptional landscape. We developed a scalable approach to sequence and quantify RNA molecules in isolated neuronal nuclei from a postmortem brain, generating 3227 sets of single-neuron data from six distinct regions of the cerebral cortex. Using an iterative clustering and classification approach, we identified 16 neuronal subtypes that were further annotated on the basis of known markers and cortical cytoarchitecture. These data demonstrate a robust and scalable method for identifying and categorizing single nuclear transcriptomes, revealing shared genes sufficient to distinguish previously unknown and orthologous neuronal subtypes as well as regional identity and transcriptomic heterogeneity within the human brain.

Mutations in the optineurin (OPTN) gene have been implicated in both familial and sporadic amyotrophic lateral sclerosis (ALS). However, the role of this protein in the central nervous system (CNS) and how it may contribute to ALS pathology are unclear. Here, we found that optineurin actively suppressed receptor-interacting kinase 1 (RIPK1)–dependent signaling by regulating its turnover. Loss of OPTN led to progressive dysmyelination and axonal degeneration through engagement of necroptotic machinery in the CNS, including RIPK1, RIPK3, and mixed lineage kinase domain–like protein (MLKL). Furthermore, RIPK1- and RIPK3-mediated axonal pathology was commonly observed in SOD1G93A transgenic mice and pathological samples from human ALS patients. Thus, RIPK1 and RIPK3 play a critical role in mediating progressive axonal degeneration. Furthermore, inhibiting RIPK1 kinase may provide an axonal protective strategy for the treatment of ALS and other human degenerative diseases characterized by axonal degeneration.

Hydrogen peroxide (H2O2) production by the electrochemical 2‐electron oxygen reduction reaction (2e− ORR) is a promising alternative to the energy‐intensive anthraquinone process, and single‐atom electrocatalysts show the unique capability of high selectivity toward 2e− ORR against the 4e− one. The extremely low surface density of the single‐atom sites and the inflexibility in manipulating their geometric/electronic configurations, however, compromise the H2O2 yield and impede further performance enhancement. Herein, we construct a family of multiatom catalysts (MACs), on which two or three single atoms are closely coordinated to form high‐density active sites that are versatile in their atomic configurations for optimal adsorption of essential *OOH species. Among them, the Cox–Ni MAC presents excellent electrocatalytic performance for 2e− ORR, in terms of its exceptionally high H2O2 yield in acidic electrolytes (28.96 mol L−1 gcat.−1 h−1) and high selectivity under acidic to neutral conditions in a wide potential region (>80%, 0–0.7 V). Operando X‐ray absorption and density functional theory analyses jointly unveil its unique trimetallic Co2NiN8 configuration, which efficiently induces an appropriate Ni–d orbital filling and modulates the *OOH adsorption, together boosting the electrocatalytic 2e− ORR capability. This work thus provides a new MAC strategy for tuning the geometric/electronic structure of active sites for 2e− ORR and other potential electrochemical processes. The multiatomic Cox–Ni multiatom catalyst shows an exceptionally high H2O2 yield in acidic electrolytes (28.96 mol L−1 gcat.−1 h−1) by oxygen reduction reaction (ORR) and selectivity under acidic to neutral conditions in a wide potential region (>80%, 0–0.7 V). In situ X‐ray absorption spectroscopy and density functional theory analyses reveal that the Co2NiN8 configuration efficiently induces an appropriate Ni–d orbital filling and achieves optimal adsorption of essential *OOH species, thus boosting the electrocatalytic 2e− ORR capability.

By testing potential sources of biological signal that drive population-level variation in single-cell gene expression, the PAGODA software enables cells to be characterized on the basis of multiple functionally relevant features such as cell type, signaling state and cell cycle state. The transcriptional state of a cell reflects a variety of biological factors, from cell-type-specific features to transient processes such as the cell cycle, all of which may be of interest. However, identifying such aspects from noisy single-cell RNA-seq data remains challenging. We developed pathway and gene set overdispersion analysis (PAGODA) to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability among measured cells.

Single-cell analysis of gene expression is increasingly important for the analysis of complex tissues, including cancer, developing organs and adult stem cell niches. Here we present a detailed protocol for quantitative gene expression analysis in single cells, by the sequencing of mRNA 5′ ends. In all, 96 cells are lysed, and their mRNA is converted to cDNA. By using a template-switching mechanism, a bar code and an upstream primer-binding sequence are introduced simultaneously with reverse transcription. All cDNA is pooled and then prepared for 5′ end sequencing, including fragmentation, adapter ligation and PCR amplification. The chief advantage of this approach is the great reduction in cost and time, afforded by the early bar-coding strategy. Compared with previous methods, it is more suitable for large-scale quantitative analysis, as well as for the characterization of transcription start sites, but it is unsuitable for the detection of alternatively spliced transcripts. Sample preparation takes 3 d, and two sets of 96 cells can be prepared in parallel. Finally, the sequencing and data analysis can take an additional 4 d altogether.

: Dysregulation of arachidonic acid (ARA) metabolism results in inflammation; however, its role in acute lung injury (ALI) remains elusive. In this study, we addressed the role of dysregulated ARA metabolism in cytochromes P450 (CYPs) /cyclooxygenase-2 (COX-2) pathways in the pathogenesis of lipopolysaccharide (LPS)-induced ALI in mice. : The metabolism of CYPs/COX-2-derived ARA in the lungs of LPS-induced ALI was investigated in C57BL/6 mice. The COX-2/sEH dual inhibitor PTUPB was used to establish the function of CYPs/COX-2 dysregulation in ALI. Primary murine macrophages were used to evaluate the underlying mechanism of PTUPB involved in the activation of NLRP3 inflammasome . : Dysregulation of CYPs/COX-2 metabolism of ARA occurred in the lungs and in primary macrophages under the LPS challenge. Decrease mRNA expression of and was observed, which metabolize ARA into epoxyeicosatrienoic acids (EETs). The expressions of COX-2 and soluble epoxide hydrolase (sEH), on the other hand, was significantly upregulated. Pre-treatment with the dual COX-2 and sEH inhibitor, PTUPB, attenuated the pathological injury of lung tissues and reduced the infiltration of inflammatory cells. Furthermore, PTUPB decreased the pro-inflammatory factors, oxidative stress, and activation of NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) inflammasome in LPS-induced ALI mice. PTUPB pre-treatment remarkably reduced the activation of macrophages and NLRP3 inflammasome . Significantly, both preventive and therapeutic treatment with PTUPB improved the survival rate of mice receiving a lethal dose of LPS. : The dysregulation of CYPs/COX-2 metabolized ARA contributes to the uncontrolled inflammatory response in ALI. The dual COX-2 and sEH inhibitor PTUPB exerts anti-inflammatory effects in treating ALI by inhibiting the NLRP3 inflammasome activation.

High-dimensional stochastic dynamical systems enforced by Poisson white noise (PWN) are encountered widely in physics, chemistry, biology, and engineering fields, but it is hard to capture the probability density function (PDF) of the quantity of interest of these systems. Recently, the dimension-reduced probability density evolution equation (DR-PDEE) has shown significant advantages in probabilistic response determination of path-continuous processes, especially for systems of high dimensions and strong nonlinearity, but there are still challenges in path-discontinuous processes, such as PWN-driven systems, due to their random jumps. In the present paper, the DR-PDEE governing the PDF of any single component of state vector of interest for a high-dimensional system enforced by PWN is established. It is always a one-dimensional partial integro-differential equation regardless of the dimension of the system if merely one single quantity is of interest. The intrinsic drift function and intrinsic rate function (the latter is for parametric excitations) in the DR-PDEE can be identified numerically based on the data from representative deterministic dynamic analyses of the PWN-driven system. Then solving the DR-PDEE numerically yields the solution of transient PDF of the quantity of interest. Numerical examples are illustrated to verify the efficiency and accuracy of the proposed method.

In this note, some points to paper (Xu L.G., Liu W.,” Hu ”H.X.:“Exponential ultimate boundedness of fractional-order differential system via periodically intermittent control” [Nonlinear Dyn 2019;92(2), 247–265) are presented. Fractional calculus is of memory property which is different from integral calculus. But this important property is neglected in the proof processes of the main theoretical achievements. We analyze these errors in Laplace domain and time domain. Lastly, some counterexamples are presented against the intermittent stability conditions in Xu et al. (Nonlinear Dyn 92(2):247–265, 2019. https://doi.org/10.1007/s11071-019-04877-y ).

Background Colorectal cancer is the 4th common cancer in China. Most colorectal cancers are due to modifiable lifestyle factors, but few studies have provided a systematic evidence-based assessment of the burden of colorectal cancer incidence and mortality attributable to the known risk factors in China. Methods We estimated the population attributable faction (PAF) for each selected risk factor in China, based on the prevalence of exposure around 2000 and relative risks from cohort studies and meta-analyses. Results Among 245,000 new cases and 139,000 deaths of colorectal cancer in China in 2012, we found that 115,578 incident cases and 63,102 deaths of colorectal cancer were attributable to smoking, alcohol drinking, overweight and obesity, physical inactivity and dietary factors. Low vegetable intake was the main risk factor for colorectal cancer with a PAF of 17.9%. Physical inactivity was responsible for 8.9% of colorectal cancer incidence and mortality. The remaining factors, including high red and processed meat intake, low fruit intake, alcohol drinking, overweight/obesity and smoking, accounted for 8.6%, 6.4%, 5.4%, 5.3% and 4.9% of colorectal cancer, respectively. Overall, 45.5% of colorectal cancer incidence and mortality were attributable to the joint effects of these seven risk factors. Conclusions Tobacco smoking, alcohol drinking, overweight or obesity, physical inactivity, low vegetable intake, low fruit intake, and high red and processed meat intake were responsible for nearly 46% of colorectal cancer incidence and mortality in China in 2012. Our findings could provide a basis for developing guidelines of colorectal cancer prevention and control in China.