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Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori 'linked' features. We describe matching X-modality via fuzzy smoothed embedding (MaxFuse), a cross-modal data integration method that, through iterative coembedding, data smoothing and cell matching, uses all information in each modality to obtain high-quality integration even when features are weakly linked. MaxFuse is modality-agnostic and demonstrates high robustness and accuracy in the weak linkage scenario, achieving 20~70% relative improvement over existing methods under key evaluation metrics on benchmarking datasets. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, MaxFuse enabled the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section., (© 2023. The Author(s).)

Persistent inflammation driven by cytokines such as type-one interferon (IFN-I) can cause immunosuppression. We show that administration of the Janus kinase 1 (JAK1) inhibitor itacitinib after anti-PD-1 (programmed cell death protein 1) immunotherapy improves immune function and antitumor responses in mice and results in high response rates (67%) in a phase 2 clinical trial for metastatic non-small cell lung cancer. Patients who failed to respond to initial anti-PD-1 immunotherapy but responded after addition of itacitinib had multiple features of poor immune function to anti-PD-1 alone that improved after JAK inhibition. Itacitinib promoted CD8 T cell plasticity and therapeutic responses of exhausted and effector memory-like T cell clonotypes. Patients with persistent inflammation refractory to itacitinib showed progressive CD8 T cell terminal differentiation and progressive disease. Thus, JAK inhibition may improve the efficacy of anti-PD-1 immunotherapy by pivoting T cell differentiation dynamics.

Aims: Regular transient limb ischemia (RTLI) can prevent atherosclerosis (AS) progression in hypercholesterolemic rabbits. This study aimed to investigate the minimum effective intensity and possible mechanisms of RTLI for preventing atherosclerosis., Methods: Eighty rabbits were divided into eight groups: normal (N), high cholesterol (H), three RTLI [three RTLI cycles every other day (R3qod), three RTLI cycles daily (R3qd), and six RTLI cycles daily (R6qd), each cycle of RTLI included 5 min of limb ischemia followed by 5 min limb reperfusion], and three correlated sham RTLI [sham ischemia for 30 min once every other day (S3qod), sham ischemia for 30 min once daily (S3qd), and sham ischemia for 60 min once daily (S6qd)]. Rabbits in group N were kept normally, while the others were fed 1% cholesterol diet for 12 weeks. The RTLI and sham RTLI groups were received RTLI or sham RTLI procedure, respectively. The plaque area in the thoracic aorta was determined by oil red O staining, and quantifying the ratio of plaque area to intimal area (PA/IA). Endothelium-dependent and -independent relaxation were also determined. Endothelial cell were isolated from abdominal aorta of rabbits, and the apoptosis ratio was detected using flow cytometry., Results: The PA/IA and early apoptotic cell ratio was significantly lower as well as the endothelium-dependent relaxation response was higher in group R6qd than those in groups H and S6qd, while those in the R3qod group was not significantly different from those in groups H and S3qod, as well as those in the R3qd group showed no significant difference compared to those in groups H and S3qd., Conclusions: Six cycles of RTLI daily was the optimal effective intensity to prevent AS progression in rabbits. Endothelial function improvement and apoptosis inhibition might contribute to the anti-AS effects., (© 2024. The Author(s).)

Type 2 diabetes (T2D) is a global public health issue characterized by excess weight, abdominal obesity, dyslipidemia, hyperglycemia, and a progressive increase in insulin resistance. Human population studies of T2D development and its effects on systemic metabolism are confounded by many factors that cannot be controlled, complicating the interpretation of results and the identification of early biomarkers. Aged, sedentary, and overweight/obese non-human primates (NHPs) are one of the best animal models to mimic spontaneous T2D development in humans. We sought to identify and distinguish a set of plasma and/or fecal metabolite biomarkers, that have earlier disease onset predictability, and that could be evaluated for their predictability in subsequent T2D studies in human cohorts. In this study, a single plasma and fecal sample was collected from each animal in a colony of 57 healthy and dysmetabolic NHPs and analyzed for metabolomics and lipidomics. The samples were comprehensively analyzed using untargeted and targeted LC/MS/MS. The changes in each animal's disease phenotype were monitored using IVGTT, HbA1c, and other clinical metrics, and correlated with their metabolic profile. The plasma and fecal lipids, as well as bile acid profiles, from Healthy, Dysmetabolic (Dys), and Diabetic (Dia) animals were compared. Following univariate and multivariate analyses, including adjustments for weight, age, and sex, several plasma lipid species were identified to be significantly different between these animal groups. Medium and long-chain plasma phosphatidylcholines (PCs) ranked highest at distinguishing Healthy from Dys animals, whereas plasma triglycerides (TG) primarily distinguished Dia from Dys animals. Random Forest (RF) analysis of fecal bile acids showed a reduction in the secondary bile acid glycoconjugate, GCDCA, in diseased animals (AUC 0.76[0.64, 0.89]). Moreover, metagenomics results revealed several bacterial species, belonging to the genera Roseburia , Ruminococcus , Clostridium , and Streptococcus , to be both significantly enriched in non-healthy animals and associated with secondary bile acid levels. In summary, our results highlight the detection of several elevated circulating plasma PCs and microbial species associated with fecal secondary bile acids in NHP dysmetabolic states. The lipids and metabolites we have identified may help researchers to differentiate individual NHPs more precisely between dysmetabolic and overtly diabetic states. This could help assign animals to study groups that are more likely to respond to potential therapies where a difference in efficacy might be anticipated between early vs. advanced disease.

Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp., (© 2024 Malamon et al.)

Lipids are structurally diverse molecules that play a pivotal role in a plethora of biological processes. However, deciphering the biological roles of the specific lipids is challenging due to the existence of numerous isomers. This high chemical complexity of the lipidome is one of the major challenges in lipidomics research, as the traditional liquid chromatography-mass spectrometry (LC-MS) based approaches are often not powerful enough to resolve these isomeric and isobaric nuances within complex samples. Thus, lipids are uniquely suited to the benefits provided by multidimensional liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS) analysis. However, many forms of lipid isomerism, including double-bond positional isomers and regioisomers, are structurally similar such that their collision cross section (CCS) differences are unresolvable via conventional IM approaches. Here we evaluate the performance of a high resolution ion mobility (HRIM) system based on structures for lossless ion manipulation (SLIM) technology interfaced to a high resolution quadrupole time-of-flight (QTOF) analyzer to address the noted lipidomic isomerism challenge. SLIM implements the traveling wave ion mobility technique along an ∼13 m ion path, providing longer path lengths to enable improved separation of isomeric features. We demonstrate the power of HRIM-MS to dissect isomeric PC standards differing only in double bond (DB) and stereospecific number (SN) positions. The partial separation of protonated DB isomers is significantly enhanced when they are analyzed as metal adducts. For sodium adducts, we achieve close to baseline separation of three different PC 18:1/18:1 isomers with different cis -double bond locations. Similarly, PC 18:1/18:1 ( cis -9) can be resolved from the corresponding PC 18:1/18:1 ( trans -9) form. The separation capacity is further enhanced when using silver ion doping, enabling the baseline separation of regioisomers that cannot be resolved when measured as sodium adducts. The sensitivity and reproducibility of the approach were assessed, and the performance for more complex mixtures was benchmarked by identifying PC isomers in total brain and liver lipid extracts.

Multimodal single-cell technologies profile multiple modalities for each cell simultaneously, enabling a more thorough characterization of cell populations. Existing dimension-reduction methods for multimodal data capture the "union of information," producing a lower-dimensional embedding that combines the information across modalities. While these tools are useful, we focus on a fundamentally different task of separating and quantifying the information among cells that is shared between the two modalities as well as unique to only one modality. Hence, we develop Tilted Canonical Correlation Analysis (Tilted-CCA), a method that decomposes a paired multimodal dataset into three lower-dimensional embeddings-one embedding captures the "intersection of information," representing the geometric relations among the cells that is common to both modalities, while the remaining two embeddings capture the "distinct information for a modality," representing the modality-specific geometric relations. We analyze single-cell multimodal datasets sequencing RNA along surface antibodies (i.e., CITE-seq) as well as RNA alongside chromatin accessibility (i.e., 10x) for blood cells and developing neurons via Tilted-CCA. These analyses show that Tilted-CCA enables meaningful visualization and quantification of the cross-modal information. Finally, Tilted-CCA's framework allows us to perform two specific downstream analyses. First, for single-cell datasets that simultaneously profile transcriptome and surface antibody markers, we show that Tilted-CCA helps design the target antibody panel to complement the transcriptome best. Second, for developmental single-cell datasets that simultaneously profile transcriptome and chromatin accessibility, we show that Tilted-CCA helps identify development-informative genes and distinguish between transient versus terminal cell types.

Background: Alveolar recruitment maneuvers (ARMs) may lead to transient hypotension, but the clinical characteristics of this induced hypotension are poorly understood. We investigated the characteristics of ARM-related hypotension in patients who underwent laparoscopic colorectal cancer resection., Aim: To investigate the characteristics of ARM-related hypotension in patients who underwent laparoscopic colorectal cancer resection., Methods: This was a secondary analysis of the PROtective Ventilation using Open Lung approach Or Not trial and included 140 subjects. An ARM was repeated every 30 min during intraoperative mechanical ventilation. The primary endpoint was ARM-related hypotension, defined as a mean arterial pressure (MAP) < 60 mmHg during an ARM or within 5 min after an ARM. The risk factors for hypotension were identified. The peri-ARM changes in blood pressure were analyzed for the first three ARMs (ARM 1,2,3 ) and the last ARM (ARM last )., Results: Thirty-four subjects (24.3%) developed ARM-related hypotension. Of all 1027 ARMs, 37 (3.61%) induced hypotension. More ARMs under nonpneumoperitoneum (33/349, 9.46%) than under pneumoperitoneum conditions (4/678, 0.59%) induced hypotension ( P < 0.01). The incidence of hypotension was higher at ARM 1 points than at non-ARM 1 points (18/135, 13.3% vs 19/892, 2.1%; P < 0.01). The median percentage decrease in the MAP at ARM 1 was 14%. Age ≥ 74 years, blood loss ≥ 150 mL and peak inspiratory pressure under pneumoperitoneum < 24 cm H 2 O were risk factors for ARM-related hypotension., Conclusion: When the ARM was repeated intraoperatively, a quarter of subjects developed ARM-related hypotension, but only 3.61% of ARMs induced hypotension. ARM-related hypotension most occurred in a hemodynamically unstable state or a hypovolemic state, and in elderly subjects. Fortunately, ARMs that were performed under pneumoperitoneum conditions had less impact on blood pressure., Competing Interests: Conflict-of-interest statement: The authors declare that there are no potential conflicts of interest with respect to the study, authorship, and/or publication of this article., (©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.)

The intestine is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota and affects overall health 1 . The intesting has a length of over nine metres, along which there are differences in structure and function 2 . The localization of individual cell types, cell type development trajectories and detailed cell transcriptional programs probably drive these differences in function. Here, to better understand these differences, we evaluated the organization of single cells using multiplexed imaging and single-nucleus RNA and open chromatin assays across eight different intestinal sites from nine donors. Through systematic analyses, we find cell compositions that differ substantially across regions of the intestine and demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighbourhoods and communities, highlighting distinct immunological niches that are present in the intestine. We also map gene regulatory differences in these cells that are suggestive of a regulatory differentiation cascade, and associate intestinal disease heritability with specific cell types. These results describe the complexity of the cell composition, regulation and organization for this organ, and serve as an important reference map for understanding human biology and disease., (© 2023. The Author(s).)

Purpose: The liver is the most frequent metastatic site for colorectal cancer. Its microenvironment is modified to provide a niche that is conducive for colorectal cancer cell growth. This study focused on characterizing the cellular changes in the metastatic colorectal cancer (mCRC) liver tumor microenvironment (TME)., Experimental Design: We analyzed a series of microsatellite stable (MSS) mCRCs to the liver, paired normal liver tissue, and peripheral blood mononuclear cells using single-cell RNA sequencing (scRNA-seq). We validated our findings using multiplexed spatial imaging and bulk gene expression with cell deconvolution., Results: We identified TME-specific SPP1-expressing macrophages with altered metabolism features, foam cell characteristics, and increased activity in extracellular matrix (ECM) organization. SPP1+ macrophages and fibroblasts expressed complementary ligand-receptor pairs with the potential to mutually influence their gene-expression programs. TME lacked dysfunctional CD8 T cells and contained regulatory T cells, indicative of immunosuppression. Spatial imaging validated these cell states in the TME. Moreover, TME macrophages and fibroblasts had close spatial proximity, which is a requirement for intercellular communication and networking. In an independent cohort of mCRCs in the liver, we confirmed the presence of SPP1+ macrophages and fibroblasts using gene-expression data. An increased proportion of TME fibroblasts was associated with the worst prognosis in these patients., Conclusions: We demonstrated that mCRC in the liver is characterized by transcriptional alterations of macrophages in the TME. Intercellular networking between macrophages and fibroblasts supports colorectal cancer growth in the immunosuppressed metastatic niche in the liver. These features can be used to target immune-checkpoint-resistant MSS tumors., (©2022 The Authors; Published by the American Association for Cancer Research.)

Background: Bacterial infection is an important cause of cholelithiasis or gallstones and interferes with its treatment. There is no consensus on bile microbial culture profiles in previous studies, and identified microbial spectrum and drug resistance is helpful for targeted preventive and therapeutic drugs in the perioperative period., Aim: To analyze the bile microbial spectrum of patients with cholelithiasis and the drug susceptibility patterns in order to establish an empirical antibiotic treatment for cholelithiasis-associated infection., Methods: A retrospective single-center study was conducted on patients diagnosed with cholelithiasis between May 2013 and December 2018., Results: This study included 185 patients, of whom 163 (88.1%) were diagnosed with gallstones and 22 (11.9%) were diagnosed with gallstones and common bile duct stones (CBDSs). Bile culture in 38 cases (20.5%) was positive. The presence of CBDSs (OR = 5.4, 95%CI: 1.3-21.9, P = 0.03) and longer operation time (> 80 min) (OR = 4.3, 95%CI: 1.4-13.1, P = 0.01) were identified as independent risk factors for positive bile culture. Gram-negative bacteria were detected in 28 positive bile specimens, and Escherichia coli ( E. coli ) (19/28) and Klebsiella pneumoniae (5/28) were the most frequently identified species. Gram-positive bacteria were present in 10 specimens. The resistance rate to cephalosporin in E. coli was above 42% and varied across generations. All the isolated E. coli strains were sensitive to carbapenems, with the exception of one imipenem-resistant strain. K. pneumoniae showed a similar resistance spectrum to E. coli . Enterococcus spp. was largely sensitive to glycopeptides and penicillin, except for a few strains of E. faecium ., Conclusion: The presence of common bile duct stones and longer operation time were identified as independent risk factors for positive bile culture in patients with cholelithiasis. The most commonly detected bacterium was E. coli . The combination of β-lactam antibiotics and β-lactamase inhibitors prescribed perioperatively appears to be effective against bile pathogens and is recommended. Additionally, regular monitoring of emerging resistance patterns is required in the future., Competing Interests: Conflict-of-interest statement: There are no conflicts of interest to report., (©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background: The postoperative length of hospital stay (PLOS) is an important indicator of surgical quality. We identified perioperative factors that affect prolonged PLOS (PPLOS) after laparoscopic colorectal cancer resection, which is the preferred surgical approach for colorectal cancer, the third most common cancer., Methods: This study was a secondary analysis of a randomized trial (clinicaltrials.gov ID: NCT03160144) that included 280 patients who underwent laparoscopic colorectal cancer resection. The primary outcome was a PPLOS, defined as a PLOS that was longer than the median PLOS. Baseline, anesthetic, surgical, and postoperative management factors were included in the univariate and multivariate analyses to identify factors influencing PPLOS., Results: The median PLOS was 10 days, and 117 patients had a PPLOS. We identified six influencing factors for PPLOS: preoperative pulse oxygen saturation < 96% (odds ratio [OR], 3.09 [95% confidence interval (CI) 1.38-6.92]; P = 0.006), distant tumor metastasis (OR, 0.34 [95% CI 0.13-0.91]; P = 0.031), the Miles procedure or left hemicolectomy (OR, 4.51 [95% CI 1.67-12.18]; P = 0.003), perioperative surgical events (OR, 2.44 [95% CI 1.25-4.76]; P = 0.009), postoperative albumin infusion (OR, 2.19 [95% CI 1.14-4.19]; P = 0.018), and postoperative early ambulation (OR, 0.35 [95% CI 0.18-0.68]; P = 0.002). Further stratified analysis showed that postoperative albumin infusion might be a risk factor for PPLOS, even in patients with a preoperative albumin level < 40 g/L (OR, 2.29 [95% CI 0.98-5.34]; P = 0.056) or duration of surgery ≥ 3 h (OR, 2.52 [95% CI 1.08-5.87]; P = 0.032)., Conclusions: A low preoperative pulse oximetry reading, complex surgical procedures, perioperative surgical events, and postoperative albumin infusion may be risk factors for PPLOS after laparoscopic colorectal cancer resection, whereas distant tumor metastasis and postoperative early ambulation might be protective factors. The association between postoperative albumin infusion, a modifiable factor, and PLOS or clinical outcomes warrants further investigation., (© 2022. The Author(s).)

Pathway analysis is a key analytical stage in the interpretation of omics data, providing a powerful method for detecting alterations in cellular processes. We recently developed a sensitive and distribution-free statistical framework for multisample distribution testing, which we implement here in the open-source R package single-cell pathway analysis (SCPA). We demonstrate the effectiveness of SCPA over commonly used methods, generate a scRNA-seq T cell dataset, and characterize pathway activity over early cellular activation. This reveals regulatory pathways in T cells, including an intrinsic type I interferon system regulating T cell survival and a reliance on arachidonic acid metabolism throughout T cell activation. A systems-level characterization of pathway activity in T cells across multiple tissues also identifies alpha-defensin expression as a hallmark of bone-marrow-derived T cells. Overall, this work provides a widely applicable tool for single-cell pathway analysis and highlights regulatory mechanisms of T cells., Competing Interests: Declaration of interests The authors declare no competing interests., (Published by Elsevier Inc.)

Glucuronidation is a common phase II metabolic process for drugs and xenobiotics which increases their solubility for excretion. Acyl glucuronides (glucuronides of carboxylic acids) present concerns as they have been implicated in gastrointestinal toxicity and hepatic failure. Despite the substantial success in the bulk analysis of these species, previous attempts using traditional mass spectrometry imaging (MSI) techniques have completely or partially failed and therefore little is known about their localization in tissues. Herein, we use nanospray desorption electrospray ionization mass spectrometry imaging (nano-DESI MSI), an ambient liquid extraction-based ionization technique, as a viable alternative to other MSI techniques to examine the localization of diclofenac, a widely used nonsteroidal anti-inflammatory drug, and its metabolites in mouse kidney and liver tissues. MSI data acquired over a broad m/z range showed low signals of the drug and its metabolites resulting from the low ionization efficiency and substantial signal suppression on the tissue. Significant improvements in the signal-to-noise were obtained using selected ion monitoring (SIM) with m/z windows centered around the low-abundance ions of interest. Using nano-DESI MSI in SIM mode, we observed that diclofenac acyl glucuronide and hydroxydiclofenac are localized to the inner medulla and cortex of the kidney, respectively, which is consistent with the previously reported localization of enzymes that process diclofenac into its respective metabolites. In contrast, a uniform distribution of diclofenac and its metabolites was observed in the liver tissue. Concentration ratios of diclofenac and hydroxydiclofenac calculated from nano-DESI MSI data are generally in agreement to those obtained using liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Collectively, our results demonstrate that nano-DESI MSI can be successfully used to image diclofenac and its primary metabolites and derive relative quantitative data from different tissue regions. Our approach will enable a better understanding of metabolic processes associated with diclofenac and other drugs that are difficult to analyze using commercially available MSI platforms., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The epigenetic control of gene expression is highly cell-type and context specific. Yet, despite its complexity, gene regulatory logic can be broken down into modular components consisting of a transcription factor (TF) activating or repressing the target gene expression through its binding to a cis-regulatory region. We propose a nonparametric approach, TRIPOD, to detect and characterize the three-way relationships between a TF, its target gene, and the accessibility of the TF's binding site using single-cell RNA and ATAC multiomic data. We apply TRIPOD to interrogate the cell-type-specific regulatory logic in peripheral blood mononuclear cells and contrast our results to detections from enhancer databases, cis-eQTL studies, ChIP-seq experiments, and TF knockdown/knockout studies. We then apply TRIPOD to mouse embryonic brain data and identify regulatory relationships, validated by ChIP-seq and PLAC-seq. Finally, we demonstrate TRIPOD on the SHARE-seq data of differentiating mouse hair follicle cells and identify lineage-specific regulation supported by histone marks and super-enhancer annotations. A record of this paper's transparent peer review process is included in the supplemental information., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

A major challenge of lipidomics is to determine and quantify the precise content of complex lipidomes to the exact lipid molecular species. Often, multiple methods are needed to achieve sufficient lipidomic coverage to make these determinations. Multiplexed targeted assays offer a practical alternative to enable quantitative lipidomics amenable to quality control standards within a scalable platform. Herein, we developed a multiplexed normal phase liquid chromatography-hydrophilic interaction chromatography multiple reaction monitoring method that quantifies lipid molecular species across over 20 lipid classes spanning wide polarities in a single 20-min run. Analytical challenges such as in-source fragmentation, isomer separations, and concentration dynamics were addressed to ensure confidence in selectivity, quantification, and reproducibility. Utilizing multiple MS/MS product ions per lipid species not only improved the confidence of lipid identification but also enabled the determination of relative abundances of positional isomers in samples. Lipid class-based calibration curves were applied to interpolate lipid concentrations and guide sample dilution. Analytical validation was performed following FDA Bioanalytical Method Validation Guidance for Industry. We report repeatable and robust quantitation of 900 lipid species measured in NIST-SRM-1950 plasma, with over 700 lipids achieving inter-assay variability below 25%. To demonstrate proof of concept for biomarker discovery, we analyzed plasma from mice treated with a glucosylceramide synthase inhibitor, benzoxazole 1. We observed expected reductions in glucosylceramide levels in treated animals but, more notably, identified novel lipid biomarker candidates from the plasma lipidome. These data highlight the utility of this qualified lipidomic platform for enabling biological discovery., Competing Interests: Conflicts of interest The authors declare that they have no competing interests on every aspect of the work., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Interferon-gamma (IFN-γ) has pleiotropic effects on cancer immune checkpoint blockade (ICB), including roles in ICB resistance. We analyzed gene expression in ICB-sensitive versus ICB-resistant tumor cells and identified a strong association between interferon-mediated resistance and expression of Ripk1, a regulator of tumor necrosis factor (TNF) superfamily receptors. Genetic interaction screening revealed that in cancer cells, RIPK1 diverted TNF signaling through NF-κB and away from its role in cell death. This promoted an immunosuppressive chemokine program by cancer cells, enhanced cancer cell survival, and decreased infiltration of T and NK cells expressing TNF superfamily ligands. Deletion of RIPK1 in cancer cells compromised chemokine secretion, decreased ARG1 + suppressive myeloid cells linked to ICB failure in mice and humans, and improved ICB response driven by CASP8-killing and dependent on T and NK cells. RIPK1-mediated resistance required its ubiquitin scaffolding but not kinase function. Thus, cancer cells co-opt RIPK1 to promote cell-intrinsic and cell-extrinsic resistance to immunotherapy., Competing Interests: Declaration of interests A.J.M. has received research funding from Merck. He is a scientific advisor for Takeda, H3Biomedicine, Xilio, and Related Sciences. A.J.M. is an inventor on patents related to the IFN pathway and an inventor on a filed patent related to modified CAR T cells. A.J.M. is a scientific founder for Dispatch Biotherapeutics., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Single cell biology has the potential to elucidate many critical biological processes and diseases, from development and regeneration to cancer. Single cell analyses are uncovering the molecular diversity of cells, revealing a clearer picture of the variation among and between different cell types. New techniques are beginning to unravel how differences in cell state-transcriptional, epigenetic, and other characteristics-can lead to different cell fates among genetically identical cells, which underlies complex processes such as embryonic development, drug resistance, response to injury, and cellular reprogramming. Single cell technologies also pose significant challenges relating to processing and analyzing vast amounts of data collected. To realize the potential of single cell technologies, new computational approaches are needed. On March 17-19, 2021, experts in single cell biology met virtually for the Keystone eSymposium "Single Cell Biology" to discuss advances both in single cell applications and technologies., (© 2021 New York Academy of Sciences.)

Analysis of the spatial distribution of metals, metalloids, and non-metals in biological tissues is of significant interest in the life sciences, helping to illuminate the function and roles these elements play within various biological pathways. Chemical imaging methods are commonly employed to address biological questions and reveal individual spatial distributions of analytes of interest. Elucidation of these spatial distributions can help determine key elemental and molecular information within the respective biological specimens. However, traditionally utilized imaging methods prove challenging for certain biological tissue analysis, especially with respect to applications that require high spatial resolution or depth profiling. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been shown to be effective for direct elemental analysis of solid materials with high levels of precision. In this work, chemical imaging using LA-ICP-MS has been applied as a powerful analytical methodology for the analysis of liver tissue samples. The proposed analytical methodology successfully produced both qualitative and quantitative information regarding specific elemental distributions within images of thin tissue sections with high levels of sensitivity and spatial resolution. The spatial resolution of the analytical methodology was innovatively enhanced, helping to broaden applicability of this technique to applications requiring significantly high spatial resolutions. This information can be used to further understand the role these elements play within biological systems and impacts dysregulation may have., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objective: The purpose of this study is to use the next-generation sequencing (NGS) technology platform to detect the methylation rate of phosphatase and tensin homolog deleted on chromosome ten ( PTEN ) promoter region in hepatocellular carcinoma (HCC) tissue samples, and to analyze the clinical significance of its correlation with the prognosis of patients receiving sorafenib treatment. Methods: The 52 pairs of tumor tissue and para-cancerous tissue samples from HCC patients treated with sorafenib alone, which were collected and preserved in the Liver Tumor Diagnosis and Research Center of the former 302 Hospital of the People's Liberation Army by the National Natural Science Foundation of China Youth Project with the project batch number 81702986 in 2018, were extracted total DNA from the samples. Then the DNA samples were treated with bisulfite and specific primers were designed to amplify the PTEN promoter region. Finally, the amplified products were analyzed by second-generation sequencing. In the analysis of clinical significance of PTEN methylation, log-rank statistical analysis was used to calculate whether there was a statistical difference in survival between the patient groups. Results: The methylation rate of PTEN promoter region in tumor tissues (29.17%±9.58%) was significantly higher than that in paracancer tissues (4.17%±2.86%)( t =19.970, P <0.05). At the same time, in HCC tissues, the methylation rate of the PTEN promoter region is negatively correlated with its expression ( F =47.270, P <0.000 1; Y =-1 800× X +38.03), and the PTEN methylation rate is negatively correlated with the prognosis of patients receiving the molecularly targeted drug Sorafenib (χ²=4.313, P <0.05). Conclusion: This study successfully established a new method for detecting methylation in the promoter region of PTEN , and the methylation rate of PTEN can be used as one of the targets of HCC diagnosis and targeted therapy.

Cancer progression is driven by both somatic copy number aberrations (CNAs) and chromatin remodeling, yet little is known about the interplay between these two classes of events in shaping the clonal diversity of cancers. We present Alleloscope, a method for allele-specific copy number estimation that can be applied to single-cell DNA- and/or transposase-accessible chromatin-sequencing (scDNA-seq, ATAC-seq) data, enabling combined analysis of allele-specific copy number and chromatin accessibility. On scDNA-seq data from gastric, colorectal and breast cancer samples, with validation using matched linked-read sequencing, Alleloscope finds pervasive occurrence of highly complex, multiallelic CNAs, in which cells that carry varying allelic configurations adding to the same total copy number coevolve within a tumor. On scATAC-seq from two basal cell carcinoma samples and a gastric cancer cell line, Alleloscope detected multiallelic copy number events and copy-neutral loss-of-heterozygosity, enabling dissection of the contributions of chromosomal instability and chromatin remodeling to tumor evolution., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: The role of the positive end-expiratory pressure (PEEP) and lung recruitment manoeuvre (LRM) combination (termed open-lung strategy, OLS) during intra-operative mechanical ventilation is not clear., Objective: To determine whether an open-lung strategy constituting medium PEEP (6-8 cmH2O) and repeated LRMs protects against postoperative complications in at-risk patients undergoing laparoscopic colorectal cancer resection under low-tidal-volume ventilation., Design: A prospective, assessor-blinded, randomised controlled trial., Setting: Single university-affiliated hospital, conducted from January 2017 to October 2018., Patients: A total of 280 patients at risk of pulmonary complications, scheduled for laparoscopic colorectal cancer resection under general anaesthesia and low-tidal-volume (6-8 ml kg-1 predicted body weight) ventilation., Intervention: The patients were randomly assigned (1 : 1) to a PEEP of 6-8 cmH2O with LRMs repeated every 30 min (OLS group) or a zero PEEP without LRMs (non-OLS group)., Main Outcome Measures: The primary outcome was a composite of major pulmonary and extrapulmonary complications occurring within 7 days after surgery. The secondary outcomes included intra-operative potentially harmful hypotension and the need for vasopressors., Results: A total of 130 patients from each group were included in the primary outcome analysis. Primary outcome events occurred in 24 patients (18.5%) in the OLS group and 43 patients (33.1%) in the non-OLS group [relative risk, 0.46; 95% confidence interval (CI), 0.26 to 0.82; P = 0.009). More patients in the OLS group developed potentially harmful hypotension (OLS vs. non-OLS, 15% vs. 4.3%; P = 0.004) and needed vasopressors (25% vs. 8.6%; P < 0.001)., Conclusion: Among at-risk patients undergoing laparoscopic colorectal cancer resection under low-tidal-volume ventilation, an open-lung strategy with a PEEP of 6-8 cmH2O and repeated LRMs reduced postoperative complications compared with a strategy using zero PEEP without LRMs. Of note, LRMs should be used with caution in patients with haemodynamic instability., Trial Registration: Clinicaltrials.gov identifier: NCT03160144., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the European Society of Anaesthesiology and Intensive Care.)

Identifying disease-related genes is of importance for understanding of molecule mechanisms of diseases, as well as diagnosis and treatment of diseases. Many computational methods have been proposed to predict disease-related genes, but how to make full use of multi-source biological data to enhance the ability of disease-gene prediction is still challenging. In this paper, we proposed a novel method for predicting disease-related genes by using fast network embedding (PrGeFNE), which can integrate multiple types of associations related to diseases and genes. Specifically, we first constructed a heterogeneous network by using phenotype-disease, disease-gene, protein-protein and gene-GO associations; and low-dimensional representation of nodes is extracted from the network by using a fast network embedding algorithm. Then, a dual-layer heterogeneous network was reconstructed by using the low-dimensional representation, and a network propagation was applied to the dual-layer heterogeneous network to predict disease-related genes. Through cross-validation and newly added-association validation, we displayed the important roles of different types of association data in enhancing the ability of disease-gene prediction, and confirmed the excellent performance of PrGeFNE by comparing to state-of-the-art algorithms. Furthermore, we developed a web tool that can facilitate researchers to search for candidate genes of different diseases predicted by PrGeFNE, along with the enrichment analysis of GO and pathway on candidate gene set. This may be useful for investigation of diseases' molecular mechanisms as well as their experimental validations. The web tool is available at http://bioinformatics.csu.edu.cn/prgefne/., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that "all genes affect every complex trait" complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved., Competing Interests: The authors have declared that no competing interests exist.

TcpC is a multifunctional virulence factor of uropathogenic E. coli (UPEC). Neutrophil extracellular trap formation (NETosis) is a crucial anti-infection mechanism of neutrophils. Here we show the influence of TcpC on NETosis and related mechanisms. We show NETosis in the context of a pyelonephritis mouse model induced by TcpC-secreting wild-type E. coli CFT073 (CFT073 wt ) and LPS-induced in vitro NETosis with CFT073 wt or recombinant TcpC (rTcpC)-treated neutrophils are inhibited. rTcpC enters neutrophils through caveolin-mediated endocytosis and inhibits LPS-induced production of ROS, proinflammatory cytokines and protein but not mRNA levels of peptidylarginine deiminase 4 (PAD4). rTcpC treatment enhances PAD4 ubiquitination and accumulation in proteasomes. Moreover, in vitro ubiquitination kit analyses show that TcpC is a PAD4-targetd E3 ubiquitin-ligase. These data suggest that TcpC inhibits NETosis primarily by serving as an E3 ligase that promotes degradation of PAD4. Our findings provide a novel mechanism underlying TcpC-mediated innate immune evasion.

Recent genetic data can offer important insights into the roles of lipoprotein subfractions and particle sizes in preventing coronary artery disease (CAD), as previous observational studies have often reported conflicting results. We used the LD score regression to estimate the genetic correlation of 77 subfraction traits with traditional lipid profile and identified 27 traits that may represent distinct genetic mechanisms. We then used Mendelian randomization (MR) to estimate the causal effect of these traits on the risk of CAD. In univariable MR, the concentration and content of medium high-density lipoprotein (HDL) particles showed a protective effect against CAD. The effect was not attenuated in multivariable analyses. Multivariable MR analyses also found that small HDL particles and smaller mean HDL particle diameter may have a protective effect. We identified four genetic markers for HDL particle size and CAD. Further investigations are needed to fully understand the role of HDL particle size., Competing Interests: QZ, JW, ZM, NZ, SH, DS, DR No competing interests declared, (© 2021, Zhao et al.)

Objective: After general anesthesia and mechanical ventilation for laparoscopic colorectal cancer resection, about 90% of patients would have different degrees of atelectasis. Authors speculated that an open-lung strategy (OLS) comprising moderate positive end-expiratory pressure (PEEP) and intermittent recruitment maneuvers (RM) can reduce atelectrauma and thus reduce the incidence of oxygenation-impairment during low-tidal-volume ventilation for laparoscopic colorectal cancer resection. The purpose of this study was to verify this hypothesis and provide a better intraoperative ventilation scheme for laparoscopic colorectal cancer resection. Methods: This was a prospectively randomized controlled clinical trial which was approved by the Ethics Committee of the Sixth Affiliated Hospital, Sun Yat-sen University (2017ZSLYEC-002), and registered at the ClinicalTrials.gov (NCT03160144). From January to July 2017, patients who underwent laparoscopic colorectal cancer resection, with age > 40 years, estimated pneumoperitoneum time ≥ 1.5 h, pulse oxygen saturation ≥ 92%, and risk grade for postoperative pulmonary complications ≥ 2 were prospectively enrolled. The patients with American Society of Anesthesiologists physical status ≥ IV, body mass index ≥ 30 kg/m(2), pneumonia, acute respiratory failure or sepsis within 1 month, severe chronic obstructive pulmonary disease, pulmonary bullae and progressive neuromuscular diseases, and those participating in other interventional clinical trials were excluded. The enrolled patients were randomly assigned (1:1) to the OLS group (with a PEEP of 6-8 cm H(2)O and intermittent RM), and the NOLS group (without using PEEP and RM). Partial pressure of arterial oxygen (PaO(2)) /fraction of inspired oxygen (FiO(2)) and shunt fraction (Q(S)/Q(T)) were calculated via arterial and central venous blood gas analysis performed at 0.5 h (T(1)), 1.5 h (T(2)) after pneumoperitoneum induction and at 20 min after admission to the recovery room. Driving pressure immediately before pneumoperitoneum induction (T(0)) and at T(2) were calculated via monitoring data. The primary outcome was oxygenation-impairment (PaO(2)/FiO(2) ≤ 300 mmHg) during mechanical ventilation. Results: In each group, 48 patients under general anesthesia and low-tidal-volume ventilation were included in the final analysis. During ventilation, the oxygenation-impairment occurred in 7 patients (14.6%) of OLS group and in 17 patients (35.4%) of NOLS group, whose difference was statistically significant between two groups (χ(2)=5.556, RR=0.31, 95%CI: 0.12 to 0.84, P =0.033). During ventilation, the patients in the OLS group had higher PaO(2)/FiO(2) [T(1): (427±103) mmHg vs. (366±109) mmHg, t =-2.826, P =0.006; T(2): (453±103) mmHg vs. (388±122) mmHg, t =-2.739, P =0.007], lower Q(S)/Q(T) [ T(1): (9.2±6.5) % vs. (12.6±7.7) %, t =2.322, P =0.022; T(2): (7.0±5.8)% vs.(10.9±9.2)%, t =2.408, P =0.019], and lower driving pressure [T(0): (6±3) cm H(2)O vs. (10±2) cm H(2)O, t =7.421, P <0.001; T(2): (13±3) cm H(2)O vs. (17±4) cm H(2)O, t =5.417, P <0.001] than those in the NOLS group, with stratistical differences in all comparisons. In recovery room, though PaO(2)/FiO(2) [(70.3±9.4) mmHg vs. (66.8±9.4) mmHg, P =0.082] was still higher and Q(S)/Q(T) [(18.6±8.3)% vs. (21.8±8.4)%, P =0.070] was still lower in the OLS group as compared to the NOLS group, the differences were not statistically significant (both P >0.05). Conclusion: The application of such an OLS during low-tidal-volume ventilation can greatly reduce the incidence of oxygenation-impairment in laparoscopic colorectal cancer resection, and such effect may last to the period of emergence from anesthesia.

Background: N-acetylneuraminic acid (Neu5Ac) is a functional metabolite involved in coronary artery disease (CAD). We aimed to evaluate the relationship between serum Neu5Ac and the risk and prognosis of acute coronary syndrome (ACS) in a real-world prospective study., Methods: Patients with suspected ACS who underwent coronary angiography were included. Serum Neu5Ac was measured at admission. Coronary lesion severity was evaluated by Gensini Score. GRACE risk stratification was performed at admission. Major adverse cardiac events (MACEs) were recorded during follow-up., Results: A total of 766 patients, including 537 with unstable angina (UAP), 100 with myocardial infarction (MI), and 129 without CAD were included. The circulating Neu5Ac level was significantly higher in patients with MI (median [1QR]: 297[220, 374] ng/ml) than in those with UAP (227 [114, 312] ng/ml) or without CAD (207 [114, 276] ng/ml; both p < 0.001). Serum level of Neu5Ac was positively correlated with age, hypertension, serum uric acid, creatinine, MB isoform of creatine kinase (CK-MB), and Gensini score (all p < 0.05). Receiver operating characteristic curve analysis showed that a higher serum Neu5Ac was potentially associated with MI and high-risk GRACE stratification in ACS patients. Logistic analysis identified only elevated serum Neu5Ac as an independent predictor of MACEs in these patients (odds ratio [OR]: 1.003, 95% confidence interval [CI]: 1.002-1.005, p < 0.001)., Conclusions: Serum Neu5Ac is associated with myocardial injury, GRACE risk category, and prognosis in ACS patients.

While single cell RNA sequencing (scRNA-seq) is invaluable for studying cell populations, cell-surface proteins are often integral markers of cellular function and serve as primary targets for therapeutic intervention. Here we propose a transfer learning framework, single cell Transcriptome to Protein prediction with deep neural network (cTP-net), to impute surface protein abundances from scRNA-seq data by learning from existing single-cell multi-omic resources.

Although scRNA-seq is now ubiquitously adopted in studies of intratumor heterogeneity, detection of somatic mutations and inference of clonal membership from scRNA-seq is currently unreliable. We propose DENDRO, an analysis method for scRNA-seq data that clusters single cells into genetically distinct subclones and reconstructs the phylogenetic tree relating the subclones. DENDRO utilizes transcribed point mutations and accounts for technical noise and expression stochasticity. We benchmark DENDRO and demonstrate its application on simulation data and real data from three cancer types. In particular, on a mouse melanoma model in response to immunotherapy, DENDRO delineates the role of neoantigens in treatment response.

The functional properties of circulating CD8 + T cells have been associated with immune control of HIV. However, viral replication occurs predominantly in secondary lymphoid tissues, such as lymph nodes (LNs). We used an integrated single-cell approach to characterize effective HIV-specific CD8 + T cell responses in the LNs of elite controllers (ECs), defined as individuals who suppress viral replication in the absence of antiretroviral therapy (ART). Higher frequencies of total memory and follicle-homing HIV-specific CD8 + T cells were detected in the LNs of ECs compared with the LNs of chronic progressors (CPs) who were not receiving ART. Moreover, HIV-specific CD8 + T cells potently suppressed viral replication without demonstrable cytolytic activity in the LNs of ECs, which harbored substantially lower amounts of CD4 + T cell-associated HIV DNA and RNA compared with the LNs of CPs. Single-cell RNA sequencing analyses further revealed a distinct transcriptional signature among HIV-specific CD8 + T cells from the LNs of ECs, typified by the down-regulation of inhibitory receptors and cytolytic molecules and the up-regulation of multiple cytokines, predicted secreted factors, and components of the protein translation machinery. Collectively, these results provide a mechanistic framework to expedite the identification of novel antiviral factors, highlighting a potential role for the localized deployment of noncytolytic functions as a determinant of immune efficacy against HIV., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Background: The tumor immune microenvironment is one of the most important prognostic factors in liver metastasis from colorectal cancer. Low-dose cyclophosphamide (CTX) is widely believed to be involved in the modulation of the immune system. However, the underlying mechanism of low-dose CTX remains unknown. This study aimed to investigate the antitumor immunity of low-dose CTX in the treatment of colon-cancer liver metastasis., Methods: Thirty mice were randomly divided into five groups. After liver metastasis was established in colon-cancer models, mice in the treatment groups were injected with low-dose CTX (20 mg/kg) at different time points. Liver and spleen tissues were examined for T-cell markers via flow cytometry. Interleukin (IL)-10 and transforming growth factor (TGF)-β1 expression levels in liver tissues were analysed by immunohistochemistry. Serum interferon (IFN)-γ and IL-10 levels were detected by enzyme-linked immunosorbent assay. An additional 20 mice were randomly allocated into two groups and the survival times were recorded., Results: The expression levels of CD4 + T cells, CD8 + T cells, and IFN-γ were down-regulated, whereas those of IL-10 and TGF-β1 were up-regulated in liver metastasis from colon cancer in mice. Furthermore, the local and systemic microenvironments of the liver were altered, which led to reduced antitumor immune responses and subsequently liver metastasis. However, treatment with low-dose CTX reversed these effects. The survival times of mice treated with low-dose CTX were significantly longer than those of the other groups., Conclusions: Low-dose CTX exerts its antitumor activity by changing the systemic and local immune microenvironments and enhancing immune regulation in mice. CTX could be used as a drug to prevent and treat liver metastasis from colon cancer., (© The Author(s) 2019. Published by Oxford University Press and Sixth Affiliated Hospital of Sun Yat-sen University.)

In data science, determining proximity between observations is critical to many downstream analyses such as clustering, classification, and prediction. However, when the data's underlying probability distribution is unclear, the function used to compute similarity between data points is often arbitrarily chosen. Here, we present a novel definition of proximity, Semblance, that uses the empirical distribution of a feature to inform the pair-wise similarity between observations. The advantage of Semblance lies in its distribution-free formulation and its ability to place greater emphasis on proximity between observation pairs that fall at the outskirts of the data distribution, as opposed to those toward the center. Semblance is a valid Mercer kernel, allowing its principled use in kernel-based learning algorithms, and for any data modality. We demonstrate its consistently improved performance against conventional methods through simulations and real case studies from diverse applications in single-cell transcriptomics, image reconstruction, and financial forecasting., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Complement dysregulation is a feature of many retinal diseases, yet mechanistic understanding at the cellular level is limited. Given this knowledge gap about which retinal cells express complement, we performed single-cell RNA sequencing on ∼92,000 mouse retinal cells and validated our results in five major purified retinal cell types. We found evidence for a distributed cell-type-specific complement expression across 11 cell types. Notably, Müller cells are the major contributor of complement activators c1s, c3, c4, and cfb. Retinal pigment epithelium (RPE) mainly expresses cfh and the terminal complement components, whereas cfi and cfp transcripts are most abundant in neurons. Aging enhances c1s, cfb, cfp, and cfi expression, while cfh expression decreases. Transient retinal ischemia increases complement expression in microglia, Müller cells, and RPE. In summary, we report a unique complement expression signature for murine retinal cell types suggesting a well-orchestrated regulation of local complement expression in the retinal microenvironment., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Single-cell RNA sequencing (scRNA-seq) data are noisy and sparse. Here, we show that transfer learning across datasets remarkably improves data quality. By coupling a deep autoencoder with a Bayesian model, SAVER-X extracts transferable gene-gene relationships across data from different labs, varying conditions and divergent species, to denoise new target datasets.

Interferon-gamma (IFNG) augments immune function yet promotes T cell exhaustion through PDL1. How these opposing effects are integrated to impact immune checkpoint blockade (ICB) is unclear. We show that while inhibiting tumor IFNG signaling decreases interferon-stimulated genes (ISGs) in cancer cells, it increases ISGs in immune cells by enhancing IFNG produced by exhausted T cells (T EX ). In tumors with favorable antigenicity, these T EX mediate rejection. In tumors with neoantigen or MHC-I loss, T EX instead utilize IFNG to drive maturation of innate immune cells, including a PD1 + TRAIL + ILC1 population. By disabling an inhibitory circuit impacting PD1 and TRAIL, blocking tumor IFNG signaling promotes innate immune killing. Thus, interferon signaling in cancer cells and immune cells oppose each other to establish a regulatory relationship that limits both adaptive and innate immune killing. In melanoma and lung cancer patients, perturbation of this relationship is associated with ICB response independent of tumor mutational burden., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Inhibition of the bile salt export pump (BSEP) may be associated with clinical drug-induced liver injury, but is poorly predicted by preclinical animal models. Here we present the development of a novel rat model using siRNA knockdown (KD) of Bsep that displayed differentially enhanced hepatotoxicity to 8 Bsep inhibitors and not to 3 Bsep noninhibitors when administered at maximally tolerated doses for 7 days. Bsep KD alone resulted in 3- and 4.5-fold increases in liver and plasma levels, respectively, of the sum of the 3 most prevalent taurine conjugated bile acids (T3-BA), approximately 90% decrease in plasma and liver glycocholic acid, and a distinct bile acid regulating gene expression pattern, without resulting in hepatotoxicity. Among the Bsep inhibitors, only asunaprevir and TAK-875 resulted in serum transaminase and total bilirubin increases associated with increases in plasma T3-BA that were enhanced by Bsep KD. Benzbromarone, lopinavir, and simeprevir caused smaller increases in plasma T3-BA, but did not result in hepatotoxicity in Bsep KD rats. Bosentan, cyclosporine A, and ritonavir, however, showed no enhancement of T3-BA in plasma in Bsep KD rats, as well as Bsep noninhibitors acetaminophen, MK-0974, or clarithromycin. T3-BA findings were further strengthened through monitoring TCA-d4 converted from cholic acid-d4 overcoming interanimal variability in endogenous bile acids. Bsep KD also altered liver and/or plasma levels of asunaprevir, TAK-875, TAK-875 acyl-glucuronide, benzbromarone, and bosentan. The Bsep KD rat model has revealed differences in the effects on bile acid homeostasis among Bsep inhibitors that can best be monitored using measures of T3-BA and TCA-d4 in plasma. However, the phenotype caused by Bsep inhibition is complex due to the involvement of several compensatory mechanisms., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Endothelial dysfunction, the initial pathogenic factor in atherosclerosis, can be alleviated via transient limb ischemia. We observed the effects of regular transient limb ischemia (RTLI) on atherosclerosis in hypercholesterolemic rabbits., Methods: Twenty-eight rabbits were randomized to control, cholesterol, sham, ischemia groups (n = 7 each) between October 2010 and March 2011. They were fed a normal diet in the control group and hypercholesterolemic diet in other groups for 12 weeks. Six cycles of RTLI were performed once per day on the ischemia group. Serum samples were prepared to measure the total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) before the experiment (W0), at the end of weeks 4, 8, 12 (W4, W8, W12). The whole aorta was harvested at W12 and stained using Sudan IV to identify the plaque. The plaque area was measured using Image J. Results were analyzed by analysis of variance or rank sum test., Results: Concentrations of TC in the cholesterol group were higher than those in the control group at W4 (29.60 [23.75, 39.30] vs. 1.00 [0.80, 1.55], Z = -2.745, P = 0.006), W8 (41.78 [28.08, 47.37] vs. 0.35 [0.10, 0.68], Z = -2.739, P = 0.006), W12 (48.32 [40.04, 48.95] vs. 0.61 [0.50, 0.86], Z = -2.739, P = 0.006). Similar results were obtained for HDL-C and LDL-C. Serum concentrations of TC, HDL-C, and LDL-C in the hypercholesterolemic groups had no differences (all P > 0.05). The percentage of plaque area in the cholesterol group was higher than that in the control group (47.22 ± 23.89% vs. 0, Z = -2.986, P = 0.003). Square root of the percentage of plaque area was smaller in the ischemia group than that in the cholesterol (0.44 ± 0.13 vs. 0.67 ± 0.18, P = 0.014) or sham groups (0.44 ± 0.13 vs. 0.61 ± 0.12, P = 0.049)., Conclusion: In hypercholesterolemic rabbits, RTLI might prevent atherosclerosis progression by reducing the percentage of plaque area.

Knowledge of cell type composition in disease relevant tissues is an important step towards the identification of cellular targets of disease. We present MuSiC, a method that utilizes cell-type specific gene expression from single-cell RNA sequencing (RNA-seq) data to characterize cell type compositions from bulk RNA-seq data in complex tissues. By appropriate weighting of genes showing cross-subject and cross-cell consistency, MuSiC enables the transfer of cell type-specific gene expression information from one dataset to another. When applied to pancreatic islet and whole kidney expression data in human, mouse, and rats, MuSiC outperformed existing methods, especially for tissues with closely related cell types. MuSiC enables the characterization of cellular heterogeneity of complex tissues for understanding of disease mechanisms. As bulk tissue data are more easily accessible than single-cell RNA-seq, MuSiC allows the utilization of the vast amounts of disease relevant bulk tissue RNA-seq data for elucidating cell type contributions in disease.

Inferring figure-ground organization in two-dimensional images may require different complementary strategies. For isolated objects, it has been shown that mechanisms in visual cortex exploit the overall distribution of contours, but in images of cluttered scenes where the grouping of contours is not obvious, that strategy would fail. However, natural scenes contain local features, specifically contour junctions, that may contribute to the definition of object regions. To study the role of local features in the assignment of border ownership, we recorded single-cell activity from visual cortex in awake behaving Macaca mulatta. We tested configurations perceived as two overlapping figures in which T- and L-junctions depend on the direction of overlap, whereas the overall distribution of contours provides no valid information. While recording responses to the occluding contour, we varied direction of overlap and variably masked some of the critical contour features to determine their influences and their interactions. On average, most features influenced the responses consistently, producing either enhancement or suppression depending on border ownership. Different feature types could have opposite effects even at the same location. Features far from the receptive field produced effects as strong as near features and with the same short latency. Summation was highly nonlinear: any single feature produced more than two-thirds of the effect of all features together. These findings reveal fast and highly specific organization mechanisms, supporting a previously proposed model in which "grouping cells" integrate widely distributed edge signals with specific end-stopped signals to modulate the original edge signals by feedback. NEW & NOTEWORTHY Seeing objects seems effortless, but defining objects in a scene requires sophisticated neural mechanisms. For isolated objects, the visual cortex groups contours based on overall distribution, but this strategy does not work for cluttered scenes. Here, we demonstrate mechanisms that integrate local contour features like T- and L-junctions to resolve clutter. The process is fast, evaluates widely distributed features, and gives any single feature a decisive influence on figure-ground representation.

In observational studies to estimate treatment effects, unmeasured confounding is often a concern. The instrumental variable (IV) method can control for unmeasured confounding when there is a valid IV. To be a valid IV, a variable needs to be independent of unmeasured confounders and only affect the outcome through affecting the treatment. When applying the IV method, there is often concern that a putative IV is invalid to some degree. We present an approach to sensitivity analysis for the IV method which examines the sensitivity of inferences to violations of IV validity. Specifically, we consider sensitivity when the magnitude of association between the putative IV and the unmeasured confounders and the direct effect of the IV on the outcome are limited in magnitude by a sensitivity parameter. Our approach is based on extending the Anderson-Rubin test and is valid regardless of the strength of the instrument. A power formula for this sensitivity analysis is presented. We illustrate its usage via examples about Mendelian randomization studies and its implications via a comparison of using rare versus common genetic variants as instruments., (© 2018, The International Biometric Society.)

High-throughput DNA sequencing enables detection of copy number variations (CNVs) on the genome-wide scale with finer resolution compared to array-based methods but suffers from biases and artifacts that lead to false discoveries and low sensitivity. We describe CODEX2, as a statistical framework for full-spectrum CNV profiling that is sensitive for variants with both common and rare population frequencies and that is applicable to study designs with and without negative control samples. We demonstrate and evaluate CODEX2 on whole-exome and targeted sequencing data, where biases are the most prominent. CODEX2 outperforms existing methods and, in particular, significantly improves sensitivity for common CNVs.

Currently, there is a lack of software for detecting copy number variations and constructing copy number profile for the whole genome from single-cell DNA sequencing data, which are often of low coverage and high technical noises. Here we introduce a new toolkit, SCNV, which features an efficient bin-free segmentation approach and provides the highest resolution possible for breakpoint detection and the subsequent copy number calling. SCNV can auto-tune parameters based on a set of normal cells from the same batch to adjust for the technical noise level of the data, facilitating its application to data gathered from different platforms and different studies.

Motivation: Copy number variations (CNVs) are gains and losses of DNA segments and have been associated with disease. Many large-scale genetic association studies are performing CNV analysis using whole exome sequencing (WES) and whole genome sequencing (WGS). In many of these studies, previous single-nucleotide polymorphism (SNP)-array data are available. An integrated cross-platform analysis is expected to improve resolution and accuracy, yet there is no tool for effectively combining data from sequencing and array platforms. The detection of CNVs using sequencing data alone can also be further improved by the utilization of allele-specific reads., Results: We propose a statistical framework, integrated CNV (iCNV) detection algorithm, which can be applied to multiple study designs: WES only, WGS only, SNP array only, or any combination of SNP and sequencing data. iCNV applies platform-specific normalization, utilizes allele specific reads from sequencing and integrates matched NGS and SNP-array data by a hidden Markov model. We compare integrated two-platform CNV detection using iCNV to naïve intersection or union of platforms and show that iCNV increases sensitivity and robustness. We also assess the accuracy of iCNV on WGS data only and show that the utilization of allele-specific reads improve CNV detection accuracy compared to existing methods., Availability and Implementation: https://github.com/zhouzilu/iCNV., Supplementary Information: Supplementary data are available at Bioinformatics online.

Single-cell RNA sequencing (scRNA-seq) enables the quantification of each gene's expression distribution across cells, thus allowing the assessment of the dispersion, nonzero fraction, and other aspects of its distribution beyond the mean. These statistical characterizations of the gene expression distribution are critical for understanding expression variation and for selecting marker genes for population heterogeneity. However, scRNA-seq data are noisy, with each cell typically sequenced at low coverage, thus making it difficult to infer properties of the gene expression distribution from raw counts. Based on a reexamination of nine public datasets, we propose a simple technical noise model for scRNA-seq data with unique molecular identifiers (UMI). We develop deconvolution of single-cell expression distribution (DESCEND), a method that deconvolves the true cross-cell gene expression distribution from observed scRNA-seq counts, leading to improved estimates of properties of the distribution such as dispersion and nonzero fraction. DESCEND can adjust for cell-level covariates such as cell size, cell cycle, and batch effects. DESCEND's noise model and estimation accuracy are further evaluated through comparisons to RNA FISH data, through data splitting and simulations and through its effectiveness in removing known batch effects. We demonstrate how DESCEND can clarify and improve downstream analyses such as finding differentially expressed genes, identifying cell types, and selecting differentiation markers., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable quantification of genes with low or moderate expression, which hinders downstream analysis. To address this challenge, we developed SAVER (single-cell analysis via expression recovery), an expression recovery method for unique molecule index (UMI)-based scRNA-seq data that borrows information across genes and cells to provide accurate expression estimates for all genes.