Machine learning methods for the study of cybersickness: a systematic review

This systematic review offers a world-first critical analysis of machine learning methods and systems, along with future directions for the study of cybersickness induced by virtual reality (VR). VR is becoming increasingly popular and is an important part of current advances in human training, therapies, entertainment, and access to the metaverse. Usage of this technology is limited by cybersickness, a common debilitating condition experienced upon VR immersion. Cybersickness is accompanied by a mix of symptoms including nausea, dizziness, fatigue and oculomotor disturbances. Machine learning can be used to identify cybersickness and is a step towards overcoming these physiological limitations. Practical implementation of this is possible with optimised data collection from wearable devices and appropriate algorithms that incorporate advanced machine learning approaches. The present systematic review focuses on 26 selected studies. These concern machine learning of biometric and neuro-physiological signals obtained from wearable devices for the automatic identification of cybersickness. The methods, data processing and machine learning architecture, as well as suggestions for future exploration on detection and prediction of cybersickness are explored. A wide range of immersion environments, participant activity, features and machine learning architectures were identified. Although models for cybersickness detection have been developed, literature still lacks a model for the prediction of first-instance events. Future research is pointed towards goal-oriented data selection and labelling, as well as the use of brain-inspired spiking neural network models to achieve better accuracy and understanding of complex spatio-temporal brain processes related to cybersickness

Functional Profiling of Transcription Factor Genes in Neurospora crassa.

Regulation of gene expression by DNA-binding transcription factors is essential for proper control of growth and development in all organisms. In this study, we annotate and characterize growth and developmental phenotypes for transcription factor genes in the model filamentous fungus Neurospora crassa We identified 312 transcription factor genes, corresponding to 3.2% of the protein coding genes in the genome. The largest class was the fungal-specific Zn2Cys6 (C6) binuclear cluster, with 135 members, followed by the highly conserved C2H2 zinc finger group, with 61 genes. Viable knockout mutants were produced for 273 genes, and complete growth and developmental phenotypic data are available for 242 strains, with 64% possessing at least one defect. The most prominent defect observed was in growth of basal hyphae (43% of mutants analyzed), followed by asexual sporulation (38%), and the various stages of sexual development (19%). Two growth or developmental defects were observed for 21% of the mutants, while 8% were defective in all three major phenotypes tested. Analysis of available mRNA expression data for a time course of sexual development revealed mutants with sexual phenotypes that correlate with transcription factor transcript abundance in wild type. Inspection of this data also implicated cryptic roles in sexual development for several cotranscribed transcription factor genes that do not produce a phenotype when mutated

Connecting Hospitalized Patients with Their Families: Case Series and Commentary

The overall aim of this project was to ascertain the utilization of a custom-designed telemedicine service for patients to maintain close contact (via videoconference) with family and friends during hospitalization. We conducted a retrospective chart review of hospitalized patients (primarily children) with extended hospital length of stays. Telecommunication equipment was used to provide videoconference links from the patient's bedside to friends and family in the community. Thirty-six cases were managed during a five-year period (2006 to 2010). The most common reasons for using Family-Link were related to the logistical challenges of traveling to and from the hospital—principally due to distance, time, family commitments, and/or personal cost. We conclude that videoconferencing provides a solution to some barriers that may limit family presence and participation in care for hospitalized patients, and as a patient-centered innovation is likely to enhance patient and family satisfaction

Acetylation of C/EBP alpha inhibits its granulopoietic function

CCAAT/enhancer-binding protein alpha (C/EBP alpha) is an essential transcription factor for myeloid lineage commitment. Here we demonstrate that acetylation of C/EBP alpha at lysine residues K298 and K302, mediated at least in part by general control non-derepressible 5 (GCN5), impairs C/EBP alpha DNA-binding ability and modulates C/EBP alpha transcriptional activity. Acetylated C/EBP alpha is enriched in human myeloid leukaemia cell lines and acute myeloid leukaemia (AML) samples, and downregulated upon granulocyte-colony stimulating factor (G-CSF)-mediated granulocytic differentiation of 32Dcl3 cells. C/EBP alpha mutants that mimic acetylation failed to induce granulocytic differentiation in C/EBP alpha-dependent assays, in both cell lines and in primary hematopoietic cells. Our data uncover GCN5 as a negative regulator of C/EBP alpha and demonstrate the importance of C/EBP alpha acetylation in myeloid differentiation

Can plastid genome sequencing be used for species identification in the Lauraceae?

Using DNA barcoding for species identification remains challenging for many plant groups. New sequencing approaches such as complete plastid genome sequencing may provide some increased power and practical benefits for species identification beyond standard plant DNA barcodes. We undertook a case study comparing standard DNA barcoding to plastid genome sequencing for species discrimination in the ecologically and economically important family Lauraceae, using 191 plastid genomes for 131 species from 25 genera, representing the largest plastome data set for Lauraceae to date. We found that the plastome sequences were useful in correcting some identification errors and for finding new and cryptic species. However, plastome data overall were only able to discriminate c. 60% of the species in our sample, with this representing a modest improvement from 40 to 50% discrimination success with the standard plant DNA barcodes. Beyond species discrimination, the plastid genome sequences revealed complex relationships in the family, with 12/25 genera being non-monophyletic and with extensive incongruence relative to nuclear ribosomal DNA. These results highlight that although useful for improving phylogenetic resolution in the family and providing some species-level insights, plastome sequences only partially improve species discrimination, and this reinforces the need for large-scale nuclear data to improve discrimination among closely related species

Seoul Virus and Hantavirus Disease, Shenyang, People’s Republic of China

This outbreak was caused by the virus circulating in local wild rats through infection of laboratory rats