The relevance of CT-based geometric and radiomics analysis of whole liver tumor burden to predict survival of patients with metastatic colorectal cancer.

OBJECTIVES: To investigate the prediction of 1-year survival (1-YS) in patients with metastatic colorectal cancer with use of a systematic comparative analysis of quantitative imaging biomarkers (QIBs) based on the geometric and radiomics analysis of whole liver tumor burden (WLTB) in comparison to predictions based on the tumor burden score (TBS), WLTB volume alone, and a clinical model. METHODS: A total of 103 patients (mean age: 61.0 ± 11.2 years) with colorectal liver metastases were analyzed in this retrospective study. Automatic segmentations of WLTB from baseline contrast-enhanced CT images were used. Established biomarkers as well as a standard radiomics model building were used to derive 3 prognostic models. The benefits of a geometric metastatic spread (GMS) model, the Aerts radiomics prior model of the WLTB, and the performance of TBS and WLTB volume alone were assessed. All models were analyzed in both statistical and predictive machine learning settings in terms of AUC. RESULTS: TBS showed the best discriminative performance in a statistical setting to discriminate 1-YS (AUC = 0.70, CI: [0.56, 0.90]). For the machine learning-based prediction for unseen patients, both a model of the GMS of WLTB (0.73, CI: [0.60, 0.84]) and the Aerts radiomics prior model (0.76, CI: [0.65, 0.86]) applied on the WLTB showed a numerically higher predictive performance than TBS (0.68, CI: [0.54, 0.79]), radiomics (0.65, CI: [0.55, 0.78]), WLTB volume alone (0.53, CI: [0.40. 0.66]), or the clinical model (0.56, CI: [0.43, 0.67]). CONCLUSIONS: The imaging-based GMS model may be a first step towards a more fine-grained machine learning extension of the TBS concept for risk stratification in mCRC patients without the vulnerability to technical variance of radiomics. KEY POINTS: • CT-based geometric distribution and radiomics analysis of whole liver tumor burden in metastatic colorectal cancer patients yield prognostic information. • Differences in survival are possibly attributable to the spatial distribution of metastatic lesions and the geometric metastatic spread analysis of all liver metastases may serve as robust imaging biomarker invariant to technical variation. • Imaging-based prediction models outperform clinical models for 1-year survival prediction in metastatic colorectal cancer patients with liver metastases.

Examining the Use of Autonomous Systems for Home Health Support Using a Smart Mirror.

The home is becoming a key location for healthcare delivery, including the use of technology driven by autonomous systems (AS) to monitor and support healthcare plans. Using the example of a smart mirror, this paper describes the outcomes of focus groups with people with multiple sclerosis (MS; n = 6) and people who have had a stroke (n = 15) to understand their attitudes towards the use of AS for healthcare in the home. Qualitative data were analysed using a thematic analysis. The results indicate that the use of such technology depends on the level of adaptability and responsiveness to users' specific circumstances, including their relationships with the healthcare system. A smart mirror would need to support manual entry, responsive goal setting, the effective aggregation of data sources and integration with other technology, have a range of input methods, be supportive rather than prescriptive in messaging, and give the user full control of their data. The barriers to its adoption include a perceived lack of portability and practicality, a lack of accessibility and inclusivity, a sense of redundancy, feeling overwhelmed by multiple technological devices, and a lack of trust in data sharing. These results inform the development and deployment of future health technologies based on the lived experiences of people with health conditions who require ongoing care.

Room to breathe: Using adaptive architecture to examine the relationship between alexithymia and interoception.

OBJECTIVE: Individuals with alexithymia experience difficulties interpreting emotional states in self and others, which has been associated with interoceptive impairment. Current theories are primarily based on subjective and conscious measures of interoceptive sensitivity, such as heartrate detection, but it is unclear whether similar observations would be found for objective or implicit psychophysiological measures. The present exploratory study assesses the potential of a novel assay through the use of adaptive immersive architecture [ExoBuilding]. METHODS: N = 88 participants were screened for alexithymic traits and N = 27 individuals, representing the range of scores, were sampled to participate in the behavioural task. In a repeated-measures design, participants were placed within ExoBuilding and asked to match their respiration to its movement. Performance was compared to a two-dimensional pacer condition. Behavioural (accuracy) and psychophysiological (Respiratory Sinus Arrhythmia [RSA] and heartrate) measures were compared across conditions, and also related to individual alexithymic traits. RESULTS: Participants with higher levels of alexithymia performed less accurately than participants with lower levels, in both conditions. High-alexithymia participants showed a smaller reduction in heartrate over the course of the ExoBuilding condition than low-alexithymia participants, although there were no differences in RSA between conditions or participants. CONCLUSION: Alexithymia extends beyond conscious interoceptive activities and is also observed in immersive contexts that usually exert psychophysiological effects on typical occupants. These initial findings highlight the importance of considering both conscious and implicit measures of interoception, and we suggest ways in which theories of alexithymia might benefit from capturing this distinction.

GNPS-guided discovery of xylacremolide C and D, evaluation of their putative biosynthetic origin and bioactivity studies of xylacremolide A and B.

Targeted HRMS2-GNPS-based metabolomic analysis of Pseudoxylaria sp. X187, a fungal antagonist of the fungus-growing termite symbiosis, resulted in the identification of two lipopeptidic congeners of xylacremolides, named xylacremolide C and D, which are built from d-phenylalanine, l-proline and an acetyl-CoA starter unit elongated by four malonyl-CoA derived ketide units. The putative xya gene cluster was identified from a draft genome generated by Illumina and PacBio sequencing and RNAseq studies. Biological activities of xylacremolide A and B were evaluated and revealed weak histone deacetylase inhibitory (HDACi) and antifungal activities, as well as moderate protease inhibition activity across a panel of nine human, viral and bacterial proteases.

Quantitative Imaging Biomarkers of the Whole Liver Tumor Burden Improve Survival Prediction in Metastatic Pancreatic Cancer.

Finding prognostic biomarkers with high accuracy in patients with pancreatic cancer (PC) remains a challenging problem. To improve the prediction of survival and to investigate the relevance of quantitative imaging biomarkers (QIB) we combined QIB with established clinical parameters. In this retrospective study a total of 75 patients with metastatic PC and liver metastases were analyzed. Segmentations of whole liver tumor burden (WLTB) from baseline contrast-enhanced CT images were used to derive QIBs. The benefits of QIBs in multivariable Cox models were analyzed in comparison with two clinical prognostic models from the literature. To discriminate survival, the two clinical models had concordance indices of 0.61 and 0.62 in a statistical setting. Combined clinical and imaging-based models achieved concordance indices of 0.74 and 0.70 with WLTB volume, tumor burden score (TBS), and bilobar disease being the three WLTB parameters that were kept by backward elimination. These combined clinical and imaging-based models have significantly higher predictive performance in discriminating survival than the underlying clinical models alone (p < 0.003). Radiomics and geometric WLTB analysis of patients with metastatic PC with liver metastases enhances the modeling of survival compared with models based on clinical parameters alone.

Chromatin mapping identifies BasR, a key regulator of bacteria-triggered production of fungal secondary metabolites.

The eukaryotic epigenetic machinery can be modified by bacteria to reprogram the response of eukaryotes during their interaction with microorganisms. We discovered that the bacterium Streptomyces rapamycinicus triggered increased chromatin acetylation and thus activation of the silent secondary metabolism ors gene cluster in the fungus Aspergillus nidulans. Using this model, we aim understanding mechanisms of microbial communication based on bacteria-triggered chromatin modification. Using genome-wide ChIP-seq analysis of acetylated histone H3, we uncovered the unique chromatin landscape in A. nidulans upon co-cultivation with S. rapamycinicus and relate changes in the acetylation to that in the fungal transcriptome. Differentially acetylated histones were detected in genes involved in secondary metabolism, in amino acid and nitrogen metabolism, in signaling, and encoding transcription factors. Further molecular analyses identified the Myb-like transcription factor BasR as the regulatory node for transduction of the bacterial signal in the fungus and show its function is conserved in other Aspergillus species.

Influenza A virus encoding secreted Gaussia luciferase as useful tool to analyze viral replication and its inhibition by antiviral compounds and cellular proteins.

Reporter genes inserted into viral genomes enable the easy and rapid quantification of virus replication, which is instrumental to efficient in vitro screening of antiviral compounds or in vivo analysis of viral spread and pathogenesis. Based on a published design, we have generated several replication competent influenza A viruses carrying either fluorescent proteins or Gaussia luciferase. Reporter activity could be readily quantified in infected cultures, but the virus encoding Gaussia luciferase was more stable than viruses bearing fluorescent proteins and was therefore analyzed in detail. Quantification of Gaussia luciferase activity in the supernatants of infected culture allowed the convenient and highly sensitive detection of viral spread, and enzymatic activity correlated with the number of infectious particles released from infected cells. Furthermore, the Gaussia luciferase encoding virus allowed the sensitive quantification of the antiviral activity of the neuraminidase inhibitor (NAI) zanamivir and the host cell interferon-inducible transmembrane (IFITM) proteins 1-3, which are known to inhibit influenza virus entry. Finally, the virus was used to demonstrate that influenza A virus infection is sensitive to a modulator of endosomal cholesterol, in keeping with the concept that IFITMs inhibit viral entry by altering cholesterol levels in the endosomal membrane. In sum, we report the characterization of a novel influenza A reporter virus, which allows fast and sensitive detection of viral spread and its inhibition, and we show that influenza A virus entry is sensitive to alterations of endosomal cholesterol levels.