Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

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Bench to bedside: recent advances in lung cancer pathological research with implications for diagnostic clinical practice

After decades of relative stagnation lung cancer is emerging as a disease type where rapid progress is being made in diagnosis and therapy, as well as in our understanding of disease biology. Much of this progress is of immediate impact to diagnosticians, and more is likely to affect diagnostic practice in the near future. In this review we seek to briefly summarize several key areas of active research of immediate or probable imminent value to trainee and consultant pulmonary pathologists alike. We cover some major changes in tumour classification, grading, and patient stratification, as well as considering the state of the art in machine-assisted interpretation of lung cancer histology, and the use of genetically modified lung cancer models.     

Recall of emotional and neutral words and paragraphs in traumatic brain injury

Background: Traumatic brain injury (TBI) results in verbal recall deficits and impaired processing of emotion encoded in facial appearance, prosody and the linguistic content of messages. Emotion facilitates memory (emotional memory advantage) for non-brain injured (NBI) individuals but the impact of emotion on verbal recall for linguistically encoded stimuli in TBI has not been explored.

Aims: The purpose of this study was to determine the effects of stimulus emotional content on verbal recall of words and paragraphs in TBI compared to NBI individuals.

Methods and procedures: Six 10-item lists, each with five emotional and five neutral words, and six paragraphs (three emotional, three neutral) were counterbalanced and presented in random order to 20 individuals with TBI and 44 NBI. The number of words from lists and the number of content units from paragraphs were compared for the two groups.

Outcomes and results: The NBI participants recalled more words from the lists and content units from the paragraphs than the individuals with TBI. Both groups recalled significantly more emotional than neutral words. NBI but not TBI participants had significantly greater recall for information in paragraphs with emotional content.

Conclusions: Participants with TBI showed impaired recall of words and paragraph content. Emotion facilitated word and paragraph content recall for neurotypical individuals but emotional memory advantage was limited to words for the TBI participants.     

Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study

IntroductionPredicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individualized treatment. Whole-slide images (WSIs) of tumor tissues reflect the histopathologic information of the tumor, which is important for therapeutic response effectiveness. In this study, we aimed to investigate whether predictive information for pCR could be detected from WSIs.Materials and methodsWe retrospectively collected data from four cohorts of 874 patients diagnosed with biopsy-proven breast cancer. A deep learning pathological model (DLPM) was constructed to predict pCR using biopsy WSIs in the primary cohort, and it was then validated in three external cohorts. The DLPM could generate a deep learning pathological score (DLPs) for each patient; stromal tumor-infiltrating lymphocytes (TILs) were selected for comparison with DLPs.ResultsThe WSI feature-based DLPM showed good predictive performance with the highest area under the curve (AUC) of 0.72 among the cohorts. Alternatively, the combination of the DLPM and clinical characteristics offered a better prediction performance (AUC >0.70) in all cohorts. We also evaluated the performance of DLPM in three different breast subtypes with the best prediction for the triple-negative breast cancer (TNBC) subtype (AUC: 0.73). Moreover, DLPM combined with clinical characteristics and stromal TILs achieved the highest AUC in the primary cohort (AUC: 0.82) and validation cohort 1 (AUC: 0.80).ConclusionOur study suggested that WSIs integrated with deep learning could potentially predict pCR to NAC in breast cancer. The predictive performance will be improved by combining clinical characteristics. DLPs from DLPM can provide more information compared to stromal TILs for pCR prediction.     

Failed B cell survival factor trials support the importance of memory B cells in multiple sclerosis

Clinical trials are probably the most informative experiments to help an understanding of multiple sclerosis (MS) biology. Recent successes with CD20‐depleting antibodies have focused attention towards B cell subsets as important mediators in MS. The trial of tabalumab (NTC00882999), which inhibits B cell activation factor (BAFF), is reported and reviewed and this trial is contrasted with the trial on the inhibition of a proliferation‐inducing ligand (APRIL) and BAFF using atacicept (NCT00642902). Both tabalumab and atacicept induce depletion of mature B cells and inhibit antibody formation, but they fail to deplete memory B cells and do not inhibit relapsing MS. Atacicept is reported to augment memory B cell responses and may precipitate relapse, suggesting the importance of APRIL. However, BAFF inhibition can enhance peripheral blood memory B cell responses, which was not associated with augmented relapse. Although other interpretations are possible, these data further support the hypothesis that memory B cells may be of central importance in relapsing MS, as they are the major CD20+ B cell subset expressing APRIL receptors. They also suggest that quantitative and/or qualitative differences in B cell responses or other factors, such as an immune‐regulatory effect associated with APRIL, may be important in determining whether MS reactivates following neutralization of peripheral B cell maturation and survival factors.     

Immunisation with the BCG and DTPw vaccines induces different programs of trained immunity in mice

In addition to providing pathogen-specific immunity, vaccines can also confer nonspecific effects (NSEs) on mortality and morbidity unrelated to the targeted disease. Immunisation with live vaccines, such as the BCG vaccine, has generally been associated with significantly reduced all-cause infant mortality. In contrast, some inactivated vaccines, such as the diphtheria, tetanus, whole-cell pertussis (DTPw) vaccine, have been controversially associated with increased all-cause mortality especially in female infants in high-mortality settings. The NSEs associated with BCG have been attributed, in part, to the induction of trained immunity, an epigenetic and metabolic reprograming of innate immune cells, increasing their responsiveness to subsequent microbial encounters. Whether non-live vaccines such as DTPw induce trained immunity is currently poorly understood. Here, we report that immunisation of mice with DTPw induced a unique program of trained immunity in comparison to BCG immunised mice. Altered monocyte and DC cytokine responses were evident in DTPw immunised mice even months after vaccination. Furthermore, splenic cDCs from DTPw immunised mice had altered chromatin accessibility at loci involved in immunity and metabolism, suggesting that these changes were epigenetically mediated. Interestingly, changing the order in which the BCG and DTPw vaccines were co-administered to mice altered subsequent trained immune responses. Given these differences in trained immunity, we also assessed whether administration of these vaccines altered susceptibility to sepsis in two different mouse models. Immunisation with either BCG or a DTPw-containing vaccine prior to the induction of sepsis did not significantly alter survival. Further studies are now needed to more fully investigate the potential consequences of DTPw induced trained immunity in different contexts and to assess whether other non-live vaccines also induce similar changes.     

Coupling online control and inhibitory systems in children with Developmental Coordination Disorder: Goal-directed reaching

For children with Developmental Coordination Disorder (DCD), the real-time coupling between frontal executive function and online motor control has not been explored despite reported deficits in each domain. The aim of the present study was to investigate how children with DCD enlist online control under task constraints that compel the need for inhibitory control. A total of 129 school children were sampled from mainstream primary schools. Forty-two children who met research criteria for DCD were compared with 87 typically developing controls on a modified double-jump reaching task. Children within each skill group were divided into three age bands: younger (6–7 years), mid-aged (8–9), and older (10–12). Online control was compared between groups as a function of trial type (non-jump, jump, anti-jump). Overall, results showed that while movement times were similar between skill groups under simple task constraints (non-jump), on perturbation (or jump) trials the DCD group were significantly slower than controls and corrected trajectories later. Critically, the DCD group was further disadvantaged by anti-jump trials where inhibitory control was required; however, this effect reduced with age. While coupling online control and executive systems is not well developed in younger and mid-aged children, there is evidence of age-appropriate coupling in older children. Longitudinal data are needed to clarify this intriguing finding. The theoretical and applied implications of these results are discussed.