Linking repeated subjective judgments and ConvNets for multimodal assessment of the immediate living environment

The integration of alternative data extraction approaches for multimodal data, can significantly reduce modeling difficulties for the automatic location assessment. We develop a method for assessing the quality of the immediate living environment by incorporating human judgments as ground truth into a neural network for generating new synthetic data and testing the effects in surrogate hedonic models. We expect that the quality of the data will be less biased if the annotation is performed by multiple independent persons applying repeated trials which should reduce the overall error variance and lead to more robust results. Experimental results show that linking repeated subjective judgements and Deep Learning can reliably determine the quality scores and thus expand the range of information for the quality assessment. The presented method is not computationally intensive, can be performed repetitively and can also be easily adapted to machine learning approaches in a broader sense or be transferred to other use cases. Following aspects are essential for the implementation of the method:•Sufficient amount of representative data for human assessment.•Repeated assessment trials by individuals.•Confident derivation of the effect of human judgments on property price as an approbation for further generation of synthetic data.

Exploration of spatial distribution of brain metastasis from small cell lung cancer and identification of metastatic risk level of brain regions: a multicenter, retrospective study

Objectives

This study aimed to explore the spatial distribution of brain metastases (BMs) from small cell lung cancer (SCLC) a homogenous sample, and to identify the metastatic risk levels in brain regions.

Methods

T1-enhanced magnetic resonance imaging (MRI) from SCLC patients were retrospectively reviewed from three medical institutions in China. All images were registered to the standard brain template provided by the Montreal Neurological Institute (MNI) 152 database, followed by transformation of the location of all BMs to the space of standard brain. The MNI structural atlas and Anatomical Automatic Labeling (AAL) atlas were then used to identify the anatomical brain regions, and the observed and expected rates of BMs were compared using 2-tailed proportional hypothesis testing. The locations and sizes of brain lesions were analyzed after image standardization.

Results

A total of 215 eligible patients with 1033 lesions were screened by MRI, including 157 (73%) males and 58 (27%) females. The incidence of crucial structures were as follows: hippocampus 0.68%, parahippocampal 0.97%, brainstem 2.05%, cauate 0.68%, putamen 0.68%, pallidum 0.2%, thalamus 1.36%. No BMs were found in the amygdala, pituitary gland, or pineal gland. The cumulative frequency of the important structures was 6.62%. Based on the results of MNI structural atlas, the cerebellum, deep white matter and brainstem was identified as a higher risk region than expected for BMs (P = 9.80 ×10⁻¹⁵, 9.04 ×10⁻⁶), whereas temporal lobe were low-risk regions (P = 1.65 ×10⁻⁴). More detailed AAL atlas revealed that the low-risk regions for BMs was inferior frontal gyrus (P = 6.971 ×10⁻⁴), while the high-risk regions for BMs was cerebellar hemispheres (P = 1.177 ×10⁻⁹).

Conclusion

Many crucial structures including the hippocampus, parahippocampus, pituitary gland and thalamus etc. have low frequency of brain metastases in a population of SCLC patients. This study provides the help to investigate the clinical feasibility of HA-WBRT and non-uniform dose of PCI in a population of SCLC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-021-00410-w.

5-methylcytosine and its derivatives

Epigenetics has undergone an explosion in the past decade. DNA methylation, consisting of the addition of a methyl group at the fifth position of cytosine (5-methylcytosine, 5-mC) in a CpG dinucleotide, is a well-recognized epigenetic mark with important functions in cellular development and pathogenesis. Numerous studies have focused on the characterization of DNA methylation marks associated with disease development as they may serve as useful biomarkers for diagnosis, prognosis, and prediction of response to therapy. Recently, novel cytosine modifications with potential regulatory roles such as 5-hydroxymethylcytosine (5-hmC), 5-formylcytosine (5-foC), and 5-carboxylcytosine (5-caC) have been discovered. Study of the functions of 5-mC and its oxidation derivatives promotes the understanding of the mechanism underlying association of epigenetic modifications with disease biology. In this respect, much has been accomplished in the development of methods for the discovery, detection, and location analysis of 5-mC and its oxidation derivatives. In this review, we focus on the recent advances for the global detection and location study of 5-mC and its oxidation derivatives 5-hmC, 5-foC, and 5-caC.