Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review.

BACKGROUND: The widespread use of immune checkpoint inhibitors (ICIs) has revolutionised treatment of multiple cancer types. However, selecting patients who may benefit from ICI remains challenging. Artificial intelligence (AI) approaches allow exploitation of high-dimension oncological data in research and development of precision immuno-oncology. MATERIALS AND METHODS: We conducted a systematic literature review of peer-reviewed original articles studying the ICI efficacy prediction in cancer patients across five data modalities: genomics (including genomics, transcriptomics, and epigenomics), radiomics, digital pathology (pathomics), and real-world and multimodality data. RESULTS: A total of 90 studies were included in this systematic review, with 80% published in 2021-2022. Among them, 37 studies included genomic, 20 radiomic, 8 pathomic, 20 real-world, and 5 multimodal data. Standard machine learning (ML) methods were used in 72% of studies, deep learning (DL) methods in 22%, and both in 6%. The most frequently studied cancer type was non-small-cell lung cancer (36%), followed by melanoma (16%), while 25% included pan-cancer studies. No prospective study design incorporated AI-based methodologies from the outset; rather, all implemented AI as a post hoc analysis. Novel biomarkers for ICI in radiomics and pathomics were identified using AI approaches, and molecular biomarkers have expanded past genomics into transcriptomics and epigenomics. Finally, complex algorithms and new types of AI-based markers, such as meta-biomarkers, are emerging by integrating multimodal/multi-omics data. CONCLUSION: AI-based methods have expanded the horizon for biomarker discovery, demonstrating the power of integrating multimodal data from existing datasets to discover new meta-biomarkers. While most of the included studies showed promise for AI-based prediction of benefit from immunotherapy, none provided high-level evidence for immediate practice change. A priori planned prospective trial designs are needed to cover all lifecycle steps of these software biomarkers, from development and validation to integration into clinical practice.

Laser-induced graphene on cross-linked sodium alginate.

Laser-induced graphene (LIG) possesses desirable properties for numerous applications. However, LIG formation on biocompatible substrates is needed to further augment the integration of LIG-based technologies into nanobiotechnology. Here, LIG formation on cross-linked sodium alginate is reported. The LIG is systematically investigated, providing a comprehensive understanding of the physicochemical characteristics of the material. Raman spectroscopy, scanning electron microscopy with energy-dispersive x-ray analysis, x-ray diffraction, transmission electron microscopy, Fourier-transform infrared spectroscopy and x-ray photoelectron spectroscopy techniques confirm the successful generation of oxidized graphene on the surface of cross-linked sodium alginate. The influence of laser parameters and the amount of crosslinker incorporated into the alginate substrate is explored, revealing that lower laser speed, higher resolution, and increased CaCl2content leads to LIG with lower electrical resistance. These findings could have significant implications for the fabrication of LIG on alginate with tailored conductive properties, but they could also play a guiding role for LIG formation on other biocompatible substrates.

Modality general and modality specific coding of hedonic valence.

The pleasant or unpleasant qualities that attach to our perceptions help to determine whether we approach or avoid environmental stimuli, shaping their affordances. How do brains create this affective perceptual dimension? The traditional answer is that sensory areas serve only as conduits for external impressions that are then modulated by heteromodal limbic structures in subsequent phases. Here we raise the possibility that, in addition to these well established gain control effects, sensory systems might also have a more direct role in representing the pleasantness component of perception, as supported by several strands of recent brain imaging evidence. In conjunction with a shared valence code that is independent of its sensory origins, valence representations interleaved within sensory brain areas may support finer grained experiential distinctions between how things look, sound, feel, taste and smell good or bad to us, offering a higher dimensional space of evaluative discriminations.

Psychopathology in young adults born at extremely low birth weight.

BACKGROUND: Little is known about the long-term mental health of extremely low birth weight (ELBW) (<1000 g) survivors. We test whether young adults aged 22 to 26 years born at ELBW differ from normal birth weight (NBW) controls in self-reported levels of psychopathology. METHOD: Participants included 142 ELBW survivors (86% response) born between 1977 and 1982 to residents of central-west Ontario, Canada and 133 NBW control subjects (92% response). The Young Adult Self-Report measure was used to create five DSM-IV oriented scales aggregated to form internalizing (depressive problems, anxiety problems, avoidant personality problems) and externalizing (attention deficit-hyperactivity disorder problems and antisocial personality problems) scales. RESULTS: After adjusting for family background characteristics, mean scores for ELBW survivors were 3.02 [95% confidence interval (CI) 0.78-5.26] points higher for internalizing problems and no different, i.e. 0.00 (95% CI -1.17 to 1.17), for externalizing problems. There was a sex × group statistical interaction such that being male muted the risk for externalizing problems among those born at ELBW: -2.11 (95% CI -4.21 to -0.01). Stratifying ELBW adults as born small for gestational age (SGA) versus appropriate weight for gestational age (AGA) revealed a significant gradient of risk for levels of internalizing problems that was largest for SGA, i.e. 4.75 (95% CI 1.24-8.26), and next largest for AGA, 2.49 (95% CI 0.11-4.87), compared with NBW controls. CONCLUSIONS: Depression, anxiety and avoidant personality problems (internalizing problems) are elevated in young adulthood among ELBW survivors. This effect is relatively small overall but noticeably larger among ELBW survivors born SGA.