Ultrasensitive vibrational resonance induced by small disturbances

We have found two kinds of ultra-sensitive vibrational resonance in coupled nonlinear systems. It is particularly worth pointing out that this ultra-sensitive vibrational resonance is a transient behavior caused by transient chaos. Considering long-term response, the system will transform from transient chaos to periodic response. The pattern of vibrational resonance will also transform from ultra-sensitive vibrational resonance to conventional vibrational resonance. This article focuses on the transient ultra-sensitive vibrational resonance phenomenon. It is induced by a small disturbance of the high-frequency excitation and the initial simulation conditions, respectively. The damping coefficient and the coupling strength are the key factors to induce the ultra-sensitive vibrational resonance. By increasing these two parameters, the vibrational resonance pattern can be transformed from an ultra-sensitive vibrational resonance to a conventional vibrational resonance. The reason for different vibrational resonance patterns to occur lies in the state of the system response. The response usually presents transient chaotic behavior when the ultra-sensitive vibrational resonance appears and the plot of the response amplitude versus the controlled parameters shows a highly fractalized pattern. When the response is periodic or doubly-periodic, it usually corresponds to the conventional vibrational resonance. The ultra-sensitive vibrational resonance not only occurs at the excitation frequency, but it also occurs at some more nonlinear frequency components. The ultra-sensitive vibrational resonance as a transient behavior and the transformation of vibrational resonance patterns are new phenomena in coupled nonlinear systems

A Single-Run Next-Generation Sequencing (NGS) Assay for the Simultaneous Detection of Both Gene Mutations and Large Chromosomal Abnormalities in Patients with Myelodysplastic Syndromes (MDS) and Related Myeloid Neoplasms

Chromosomal abnormalities and somatic mutations are found in patients with myelodysplastic syndromes (MDS) and myelodysplastic/myeloproliferative neoplasms (MDS/MPN) in around 50-80% of cases. The identification of these alterations is important for the accurate diagnosis and prognostic classification of these patients. Often, an apparently normal or failed karyotype might lead to an inadequate estimation of the prognostic risk, and several strategies should be combined to solve these cases. The aim of this study was to introduce a novel next-generation sequencing (NGS)-based strategy for the simultaneous detection of all the clinically relevant genetic alterations associated with these disorders. We validated this approach on a large cohort of patients by comparing our findings with those obtained with standard-of-care methods (i.e., karyotype and SNP-arrays). We show that our platform represents a significant improvement on current strategies in defining diagnosis and risk stratification of patients with MDS and myeloid-related disorders. Myelodysplastic syndromes (MDS) and myelodysplastic/myeloproliferative neoplasms are clonal disorders that share most of their cytogenetic and molecular alterations. Despite the increased knowledge of the prognostic importance of genetics in these malignancies, next-generation sequencing (NGS) has not been incorporated into clinical practice in a validated manner, and the conventional karyotype remains mandatory in the evaluation of suspected cases. However, non-informative cytogenetics might lead to an inadequate estimation of the prognostic risk. Here, we present a novel targeted NGS-based assay for the simultaneous detection of all the clinically relevant genetic alterations associated with these disorders. We validated this platform in a large cohort of patients by performing a one-to-one comparison with the lesions from karyotype and single-nucleotide polymorphism (SNP) arrays. Our strategy demonstrated an approximately 97% concordance with standard clinical assays, showing sensitivity at least equivalent to that of SNP arrays and higher than that of conventional cytogenetics. In addition, this NGS assay was able to identify both copy-neutral loss of heterozygosity events distributed genome-wide and copy number alterations, as well as somatic mutations within significant driver genes. In summary, we show a novel NGS platform that represents a significant improvement to current strategies in defining diagnosis and risk stratification of patients with MDS and myeloid-related disorder

Replicated evidence that endophenotypic expression of schizophrenia polygenic risk is greater in healthy siblings of patients compared to controls, suggesting gene-environment interaction. The EUGEI study

Background First-degree relatives of patients with psychotic disorder have higher levels of polygenic risk (PRS) for schizophrenia and higher levels of intermediate phenotypes. Methods We conducted, using two different samples for discovery (n = 336 controls and 649 siblings of patients with psychotic disorder) and replication (n = 1208 controls and 1106 siblings), an analysis of association between PRS on the one hand and psychopathological and cognitive intermediate phenotypes of schizophrenia on the other in a sample at average genetic risk (healthy controls) and a sample at higher than average risk (healthy siblings of patients). Two subthreshold psychosis phenotypes, as well as a standardised measure of cognitive ability, based on a short version of the WAIS-III short form, were used. In addition, a measure of jumping to conclusion bias (replication sample only) was tested for association with PRS. Results In both discovery and replication sample, evidence for an association between PRS and subthreshold psychosis phenotypes was observed in the relatives of patients, whereas in the controls no association was observed. Jumping to conclusion bias was similarly only associated with PRS in the sibling group. Cognitive ability was weakly negatively and non-significantly associated with PRS in both the sibling and the control group. Conclusions The degree of endophenotypic expression of schizophrenia polygenic risk depends on having a sibling with psychotic disorder, suggestive of underlying gene–environment interaction. Cognitive biases may better index genetic risk of disorder than traditional measures of neurocognition, which instead may reflect the population distribution of cognitive ability impacting the prognosis of psychotic disorder

Examining the association between exposome score for schizophrenia and functioning in schizophrenia, siblings, and healthy controls: Results from the EUGEI study.

Background. A cumulative environmental exposure score for schizophrenia (exposome score for schizophrenia [ES-SCZ]) may provide potential utility for risk stratification and outcome prediction. Here, we investigated whether ES-SCZ was associated with functioning in patients with schizophrenia spectrum disorder, unaffected siblings, and healthy controls. Methods. This cross-sectional sample consisted of 1,261 patients, 1,282 unaffected siblings, and 1,525 healthy controls. The Global Assessment of Functioning (GAF) scale was used to assess functioning. ES-SCZ was calculated based on our previously validated method. The association between ES-SCZ and the GAF dimensions (symptom and disability) was analyzed by applying regression models in each group (patients, siblings, and controls). Additional models included polygenic risk score for schizophrenia (PRS-SCZ) as a covariate. Results. ES-SCZ was associated with the GAF dimensions in patients (symptom: B = 1.53, p-value = 0.001; disability: B = 1.44, p-value = 0.001), siblings (symptom: B = 3.07, p-value < 0.001; disability: B = 2.52, p-value < 0.001), and healthy controls (symptom: B = 1.50, p-value < 0.001; disability: B = 1.31, p-value < 0.001). The results remained the same after adjusting for PRS-SCZ. The degree of associations of ES-SCZ with both symptom and disability dimensions were higher in unaffected siblings than in patients and controls. By analyzing an independent dataset (the Genetic Risk and Outcome of Psychosis study), we replicated the results observed in the patient group. Conclusions. Our findings suggest that ES-SCZ shows promise for enhancing risk prediction and stratification in research practice. From a clinical perspective, ES-SCZ may aid in efforts of clinical characterization, operationalizing transdiagnostic clinical staging models, and personalizing clinical management