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In the past decade, single-cell technologies have revealed the heterogeneity of the tumor-immune microenvironment at the genomic, transcriptomic, and proteomic levels and have furthered our understanding of the mechanisms of tumor development. Single-cell technologies have also been used to identify potential biomarkers. However, spatial information about the tumor-immune microenvironment such as cell locations and cell–cell interactomes is lost in these approaches. Recently, spatial multi-omics technologies have been used to study transcriptomes, proteomes, and metabolomes of tumor-immune microenvironments in several types of cancer, and the data obtained from these methods has been combined with immunohistochemistry and multiparameter analysis to yield markers of cancer progression. Here, we review numerous cutting-edge spatial ‘omics techniques, their application to study of the tumor-immune microenvironment, and remaining technical challenges.

To investigate the pathogenesis of a congenital form of hepatic fibrosis, human hepatic organoids were engineered to express the most common causative mutation for Autosomal Recessive Polycystic Kidney Disease (ARPKD). Here we show that these hepatic organoids develop the key features of ARPKD liver pathology (abnormal bile ducts and fibrosis) in only 21 days. The ARPKD mutation increases collagen abundance and thick collagen fiber production in hepatic organoids, which mirrors ARPKD liver tissue pathology. Transcriptomic and other analyses indicate that the ARPKD mutation generates cholangiocytes with increased TGFβ pathway activation, which are actively involved stimulating myofibroblasts to form collagen fibers. There is also an expansion of collagen-producing myofibroblasts with markedly increased PDGFRB protein expression and an activated STAT3 signaling pathway. Moreover, the transcriptome of ARPKD organoid myofibroblasts resemble those present in commonly occurring forms of liver fibrosis. PDGFRB pathway involvement was confirmed by the anti-fibrotic effect observed when ARPKD organoids were treated with PDGFRB inhibitors. Besides providing insight into the pathogenesis of congenital (and possibly acquired) forms of liver fibrosis, ARPKD organoids could also be used to test the anti-fibrotic efficacy of potential anti-fibrotic therapies. Autosomal recessive polycystic kidney disease (ARPKD) is a genetic disorder which is associated with kidney and liver pathology, including liver fibrosis. Here the authors develop and characterize human liver organoids with a ARPKD mutation, and find that they show aspects of the pathology, including fibrosis.

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have become a powerful tool for human disease modeling and therapeutic testing. However, their use remains limited by their immaturity and heterogeneity. To characterize the source of this heterogeneity, we applied complementary single-cell RNA-seq and bulk RNA-seq technologies over time during hiPSC cardiac differentiation and in the adult heart. Using integrated transcriptomic and splicing analysis, more than half a dozen distinct single-cell populations were observed, several of which were coincident at a single time-point, day 30 of differentiation. To dissect the role of distinct cardiac transcriptional regulators associated with each cell population, we systematically tested the effect of a gain or loss of three transcription factors ( NR2F2 , TBX5 , and HEY2 ), using CRISPR genome editing and ChIP-seq, in conjunction with patch clamp, calcium imaging, and CyTOF analysis. These targets, data, and integrative genomics analysis methods provide a powerful platform for understanding in vitro cellular heterogeneity. Human induced pluripotent stem cell derived cardiomyocytes are a powerful model for cardiogenesis and disease in vitro. Here the authors comprehensively map cardiac differentiation using multiple modalities, including single-cell RNA seq and CyTOF, in cells with a gain  or loss of function in key cardiac transcription factors.

The transcription factor JUN is highly expressed in pulmonary fibrosis. Its induction in mice drives lung fibrosis, which is abrogated by administration of anti-CD47. Here, we use high-dimensional mass cytometry to profile protein expression and secretome of cells from patients with pulmonary fibrosis. We show that JUN is activated in fibrotic fibroblasts that expressed increased CD47 and PD-L1. Using ATAC-seq and ChIP-seq, we found that activation of JUN rendered promoters and enhancers of CD47 and PD-L1 accessible. We further detect increased IL-6 that amplified JUN -mediated CD47 enhancer activity and protein expression. Using an in vivo mouse model of fibrosis, we found two distinct mechanisms by which blocking IL-6, CD47 and PD-L1 reversed fibrosis, by increasing phagocytosis of profibrotic fibroblasts and by eliminating suppressive effects on adaptive immunity. Our results identify specific immune mechanisms that promote fibrosis and suggest a therapeutic approach that could be used alongside conventional anti-fibrotics for pulmonary fibrosis. Fibroblast contributions to lung fibrosis and in particular their crosstalk with immune cells in the lung are incompletely understood. Here, the authors show an overall immune suppressive environment transcriptionally controlled and maintained by fibroblasts in lung fibrosis with possible therapeutic implications.

Fibrotic diseases are not well-understood. They represent a number of different diseases that are characterized by the development of severe organ fibrosis without any obvious cause, such as the devastating diseases idiopathic pulmonary fibrosis (IPF) and scleroderma. These diseases have a poor prognosis comparable with endstage cancer and are uncurable. Given the phenotypic differences, it was assumed that the different fibrotic diseases also have different pathomechanisms. Here, we demonstrate that many endstage fibrotic diseases, including IPF; scleroderma; myelofibrosis; kidney-, pancreas-, and heart-fibrosis; and nonalcoholic steatohepatosis converge in the activation of the AP1 transcription factor c-JUN in the pathologic fibroblasts. Expression of the related AP1 transcription factor FRA2 was restricted to pulmonary artery hypertension. Induction of c-Jun in mice was sufficient to induce severe fibrosis in multiple organs and steatohepatosis, which was dependent on sustained c-Jun expression. Single cell mass cytometry revealed that c-Jun activates multiple signaling pathways in mice, including pAkt and CD47, which were also induced in human disease. αCD47 antibody treatment and VEGF or PI3K inhibition reversed various organ c-Jun–mediated fibroses in vivo. These data suggest that c-JUN is a central molecular mediator of most fibrotic conditions.

Simultaneous visualization of the relationship between multiple biomolecules and their ligands or small molecules at the nanometer scale in cells will enable greater understanding of how biological processes operate. We present here high-definition multiplex ion beam imaging (HD-MIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added structurally-unmodified small molecules. With this technology, the atomic constituents of the biomolecules themselves can be used in our system as the “tag” and we demonstrate measurements down to ~30 nm lateral resolution. We correlated the subcellular localization of the chemotherapy drug cisplatin simultaneously with five subnuclear structures. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. Unexpectedly, cells surviving multi-drug treatment with cisplatin and the BET inhibitor JQ1 demonstrated near total cisplatin exclusion from the nucleus, suggesting that selective subcellular drug relocalization may modulate resistance to this important chemotherapeutic treatment. Multiplexed high-resolution imaging techniques, such as HD-MIBI, will enable studies of biomolecules and drug distributions in biologically relevant subcellular microenvironments by visualizing the processes themselves in concert, rather than inferring mechanism through surrogate analyses. Multiplexed ion beam imaging can provide subcellular localisation information but with limited resolution. Here the authors report an ion beam imaging method with nanoscale resolution which they use to assess the subcellular distribution of cisplatin.

PLAYR (proximity ligation assay for RNA) enables highly multiplexed transcript quantification in combination with protein marker detection in single cells using flow or mass cytometry. To enable the detection of expression signatures specific to individual cells, we developed PLAYR (proximity ligation assay for RNA), a method for highly multiplexed transcript quantification by flow and mass cytometry that is compatible with standard antibody staining. When used with mass cytometry, PLAYR allowed for the simultaneous quantification of more than 40 different mRNAs and proteins. In primary cells, we quantified multiple transcripts, with the identity and functional state of each analyzed cell defined on the basis of the expression of a separate set of transcripts or proteins. By expanding high-throughput deep phenotyping of cells beyond protein epitopes to include RNA expression, PLAYR opens a new avenue for the characterization of cellular metabolism.

Background Clozapine is the most effective medication for treatment-refractory schizophrenia. However, it has a high burden of adverse events, including common adverse events such as sialorrhea. Sialorrhea can lead to severe physical complications such as aspiration pneumonia, as well as psychological complications including embarrassment and low self-esteem. Compromised adherence and treatment discontinuation can occur due to intolerability. There have been no meta-analyses examining strategies to mitigate clozapine-induced sialorrhea. Methods We systematically searched Chinese and Western research databases for randomised controlled trials examining agents for clozapine-induced sialorrhea. No limit to language or date were applied to the search. Where sufficient data for individual agents was available, pairwise meta-analyses were conducted. Results were provided as risk ratios and number needed to treat. Sensitivity analysis was conducted by study quality. Adverse events were provided as number needed to harm. Results 19 studies provided data for use in the meta-analysis. Improvement in clozapine-induced sialorrhea was seen in meta-analyses of propantheline (studies = 6, risk ratio [RR] 2.38, 95% confidence interval [CI] 1.52–3.73; number needed to treat [NNT] 3, 95% CI 1.9–2.7), diphenhydramine (studies = 5, RR 3.09, 95% CI 2.36–4.03; NNT 2, 95% CI 1.5–2.0), chlorpheniramine (studies = 2, RR 2.37, 95% CI 1.59–3.55; NNT 3, 95% CI 1.6–3.5), and benzamide derivatives (odds ratio [OR] 6.93, 95% CI 3.03–15.86). When meta-analyses were limited to high-quality studies, all these results remained significant. Single studies of benzhexol, cyproheptadine, doxepin and Kongyan Tang showed promise. Propantheline increased rates of constipation with a number needed to harm (NNH) of 9 (95% CI 4.2–204.1). Conclusion Clozapine-induced sialorrhea is a potentially serious adverse event. Included studies in this meta-analysis were limited by poor study quality. Diphenhydramine, chlorpheniramine and benzamide derivatives appear to have the best supporting evidence and lowest reported adverse events. Caution should be exercised when using propantheline given its increased risk of constipation.

Electrical impedance biosensors are powerful and continuously being developed for various biological sensing applications. In this line, the sensitivity of impedance biosensors embedded with microfluidic technologies, such as sheath flow focusing, dielectrophoretic focusing, and interdigitated electrode arrays, can still be greatly improved. In particular, reagent consumption reduction and analysis time-shortening features can highly increase the analytical capabilities of such biosensors. Moreover, the reliability and efficiency of analyses are benefited by microfluidics-enabled automation. Through the use of mature microfluidic technology, complicated biological processes can be shrunk and integrated into a single microfluidic system (e.g., lab-on-a-chip or micro-total analysis systems). By incorporating electrical impedance biosensors, hand-held and bench-top microfluidic systems can be easily developed and operated by personnel without professional training. Furthermore, the impedance spectrum provides broad information regarding cell size, membrane capacitance, cytoplasmic conductivity, and cytoplasmic permittivity without the need for fluorescent labeling, magnetic modifications, or other cellular treatments. In this review article, a comprehensive summary of microfluidics-based impedance biosensors is presented. The structure of this article is based on the different substrate material categorizations. Moreover, the development trend of microfluidics-based impedance biosensors is discussed, along with difficulties and challenges that may be encountered in the future.

Liver cancer remains a leading cause of mortality worldwide, and precise diagnostic tools are essential for effective treatment planning. Liver Tumors (LTs) vary significantly in size, shape, and location, and can present with tissues of similar intensities, making automatically segmenting and classifying LTs from abdominal tomography images crucial and challenging. This review examines recent advancements in Liver Segmentation (LS) and Tumor Segmentation (TS) algorithms, highlighting their strengths and limitations regarding precision, automation, and resilience. Performance metrics are utilized to assess key detection algorithms and analytical methods, emphasizing their effectiveness and relevance in clinical contexts. The review also addresses ongoing challenges in liver tumor segmentation and identification, such as managing high variability in patient data and ensuring robustness across different imaging conditions. It suggests directions for future research, with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular methods. This paper contributes to a comprehensive understanding of current liver tumor detection techniques, provides a roadmap for future innovations, and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.