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Identifying cell types based on expression profiles is a pillar of single cell analysis. Existing machine-learning methods identify predictive features from annotated training data, which are often not available in early-stage studies. This can lead to overfitting and inferior performance when applied to new data. To address these challenges we present scROSHI, which utilizes previously obtained cell type-specific gene lists and does not require training or the existence of annotated data. By respecting the hierarchical nature of cell type relationships and assigning cells consecutively to more specialized identities, excellent prediction performance is achieved. In a benchmark based on publicly available PBMC data sets, scROSHI outperforms competing methods when training data are limited or the diversity between experiments is large.

This study investigated the image quality and choice of ultra-high b-value of two DWI breast-MRI research applications. The study cohort comprised 40 patients (20 malignant lesions). In addition to s-DWI with two m-b-values (b50 and b800) and three e-b-values (e-b1500, e-b2000, and e-b2500), z-DWI and IR m-b1500 DWI were applied. z-DWI was acquired with the same measured b-values and e-b-values as the standard sequence. For IR m-b1500 DWI, b50 and b1500 were measured, and e-b2000 and e-b2500 were mathematically extrapolated. Three readers used Likert scales to independently analyze all ultra-high b-values (b1500-b2500) for each DWI with regards to scan preference and image quality. ADC values were measured in all 20 lesions. z-DWI was the most preferred (54%), followed by IR m-b1500 DWI (46%). b1500 was significantly preferred over b2000 for z-DWI and IR m-b1500 DWI (p = 0.001 and p = 0.002, respectively). Lesion detection was not significantly different among sequences or b-values (p = 0.174). There were no significant differences in measured ADC values within lesions between s-DWI (ADC: 0.97 [±0.09] × 10$^{-3}$ mm$^{2}$/s) and z-DWI (ADC: 0.99 [±0.11] × 10$^{-3}$ mm$^{2}$/s; p = 1.000). However, there was a trend toward lower values in IR m-b1500 DWI (ADC: 0.80 [±0.06] × 10$^{-3}$ mm$^{2}$/s) than in s-DWI (p = 0.090) and z-DWI (p = 0.110). Overall, image quality was superior and there were fewer image artifacts when using the advanced sequences (z-DWI + IR m-b1500 DWI) compared with s-DWI. Considering scan preferences, we found that the optimal combination was z-DWI with a calculated b1500, especially regarding examination time.

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique to decipher tissue composition at the single-cell level and to inform on disease mechanisms, tumor heterogeneity, and the state of the immune microenvironment. Although multiple methods for the computational analysis of scRNA-seq data exist, their application in a clinical setting demands standardized and reproducible workflows, targeted to extract, condense, and display the clinically relevant information. To this end, we designed scAmpi (Single Cell Analysis mRNA pipeline), a workflow that facilitates scRNA-seq analysis from raw read processing to informing on sample composition, clinically relevant gene and pathway alterations, and in silico identification of personalized candidate drug treatments. We demonstrate the value of this workflow for clinical decision making in a molecular tumor board as part of a clinical study.

[This corrects the article DOI: 10.1371/journal.ppat.1008477.].

Post-transplant lymphoproliferative disorder (PTLD) is a potentially fatal complication after organ transplantation frequently associated with the Epstein-Barr virus (EBV). Immunosuppressive treatment is thought to allow the expansion of EBV-infected B cells, which often express all eight oncogenic EBV latent proteins. Here, we assessed whether HLA-A2 transgenic humanized NSG mice treated with the immunosuppressant FK506 could be used to model EBV-PTLD. We found that FK506 treatment of EBV-infected mice led to an elevated viral burden, more frequent tumor formation and diminished EBV-induced T cell responses, indicative of reduced EBV-specific immune control. EBV latency III and lymphoproliferation-associated cellular transcripts were up-regulated in B cells from immunosuppressed animals, akin to the viral and host gene expression pattern found in EBV-PTLD. Utilizing an unbiased gene expression profiling approach, we identified genes differentially expressed in B cells of EBV-infected animals with and without FK506 treatment. Upon investigating the most promising candidates, we validated sCD30 as a marker of uncontrolled EBV proliferation in both humanized mice and in pediatric patients with EBV-PTLD. High levels of sCD30 have been previously associated with EBV-PTLD in patients. As such, we believe that humanized mice can indeed model aspects of EBV-PTLD development and may prove useful for the safety assessment of immunomodulatory therapies.

The ability to monitor several parameters simultaneously from distinct individual fluorescent reporter molecules facilitates the disentanglement of complex and interacting systems and opens new perspectives in areas from basic science to biopharmaceutical technology. By combining annular illumination microscopy, time-correlated single photon counting, and multichannel detection, we were able to determine 14 independent parameters from one individual fluorophore. The whole set of parameters was deduced from the few properties of the fluorescence photons, i.e., arrival time, wavelength, and polarization. With this approach, the intensity, the polarization, and the spectral dynamics can be analyzed on a nanosecond time scale and the mean values can be monitored with submillisecond time resolution. Nanosecond spectral dynamics of single molecules has been observed, to the best of our knowledge, for the first time. From our experience, we can determine all parameters for more than 30% of the illuminated fluorophores in biological samples and for more than 80% in doped polymeric films.

We apply the concept of tomography to polarization-sensitive optical microscopy of single fluorophores to determine the three-dimensional orientation of molecular absorption dipoles with isotropic sensitivity. Wide-field microscopy provides the opportunity to monitor simultaneously three-dimensional rotation and two-dimensional translation of many molecules in parallel. For orientation determination the molecules are illuminated from different directions of incidence with linearly polarized light. In each exposure the excitation along a particular projection of the absorption dipole on the electric field leads to a distinct fluorescence intensity. Five exposures are sufficient to determine the full orientation of the fluorophores. To demonstrate the potential of the method we determine the orientation and position of individual immobilized lipid membrane markers. The shot-noise-limited isotropic angular resolution is 2°. For time-resolved studies the bandwidth can be expanded up to 200 Hz.

A method to identify single molecules rapidly and with high efficiency based on simple probability considerations is proposed. In principle, any property of a detected photon in a single-molecule fluorescence experiment, e.g., emission wavelength, arrival time after pulsed excitation, and polarization, can be analyzed within the framework of the outlined methodology. Monte Carlo simulations show that less than 500 photons are needed to assign an observed single molecule to one out of four species with a confidence level higher than 99.9%. We show that single dye molecules of four different dyes embedded in a polymer film can be identified with time-correlated singlephoton counting spectrally resolved in two channels.

A number of treatments targeting VEGF or mTOR pathways have been approved for metastatic clear cell Renal Cell Carcinoma (ccRCC), but the majority of patients show disease progression after first line therapy with a very low rate of complete or long-term responders. It has been shown that miRs may play a role in prediction of treatment response in various cancer types. The aim of our study was to identify a miR signature predictive for RCC patients' response to antiangiogenic tyrosine kinase inhibitor (TKI) treatment in the first line therapy. Sequencing of 40 paired normal/tumor formalin fixed and paraffin embedded ccRCC tissues revealed separate clustering via unsupervised dendrograms. With supervised analysis, the strongest differential expression was obtained with miR-99b-5p, which was significantly lower in patients with short progression free survival (<8 months) and TKI non-responders (progressive disease patients according to RECIST) (p<0.0001, each). Validation using RTqPCR and a second patient cohort compiled from three different hospitals (n=65) showed higher expression of miR-99b-5p in complete responders, but this trend did not reach statistical significance. It is concluded that low miR-99b-5p expression analyzed with sequencing methodology may correlate with tumor progression in TKI-treated ccRCC patients.