Optimization of the Asymptotic Property of Mutual Learning Involving an Integration Mechanism of Ensemble Learning

We propose an optimization method of mutual learning which converges into the identical state of optimum ensemble learning within the framework of on-line learning, and have analyzed its asymptotic property through the statistical mechanics method.The proposed model consists of two learning steps: two students independently learn from a teacher, and then the students learn from each other through the mutual learning. In mutual learning, students learn from each other and the generalization error is improved even if the teacher has not taken part in the mutual learning. However, in the case of different initial overlaps(direction cosine) between teacher and students, a student with a larger initial overlap tends to have a larger generalization error than that of before the mutual learning. To overcome this problem, our proposed optimization method of mutual learning optimizes the step sizes of two students to minimize the asymptotic property of the generalization error. Consequently, the optimized mutual learning converges to a generalization error identical to that of the optimal ensemble learning. In addition, we show the relationship between the optimum step size of the mutual learning and the integration mechanism of the ensemble learning.Comment: 13 pages, 3 figures, submitted to Journal of Physical Society of Japa

Ensemble learning of linear perceptron; Online learning theory

Within the framework of on-line learning, we study the generalization error of an ensemble learning machine learning from a linear teacher perceptron. The generalization error achieved by an ensemble of linear perceptrons having homogeneous or inhomogeneous initial weight vectors is precisely calculated at the thermodynamic limit of a large number of input elements and shows rich behavior. Our main findings are as follows. For learning with homogeneous initial weight vectors, the generalization error using an infinite number of linear student perceptrons is equal to only half that of a single linear perceptron, and converges with that of the infinite case with O(1/K) for a finite number of K linear perceptrons. For learning with inhomogeneous initial weight vectors, it is advantageous to use an approach of weighted averaging over the output of the linear perceptrons, and we show the conditions under which the optimal weights are constant during the learning process. The optimal weights depend on only correlation of the initial weight vectors.Comment: 14 pages, 3 figures, submitted to Physical Review

HMGA1 promotes breast cancer angiogenesis supporting the stability, nuclear localization and transcriptional activity of FOXM1

Background Breast cancer is the most common malignancy in women worldwide. Among the breast cancer subtypes, triple-negative breast cancer (TNBC) is the most aggressive and the most difficult to treat. One of the master regulators in TNBC progression is the architectural transcription factor HMGA1. This study aimed to further explore the HMGA1 molecular network to identify molecular mechanisms involved in TNBC progression. Methods RNA from the MDA-MB-231 cell line, silenced for HMGA1 expression, was sequenced and, with a bioinformatic analysis, molecular partners HMGA1 could cooperate with in regulating common downstream gene networks were identified. Among the putative partners, the FOXM1 transcription factor was selected. The relationship occurring between HMGA1 and FOXM1 was explored by qRT-PCR, co-immunoprecipitation and protein stability assays. Subsequently, the transcriptional activity of HMGA1 and FOXM1 was analysed by luciferase assay on the VEGFA promoter. The impact on angiogenesis was assessed in vitro, evaluating the tube formation ability of endothelial cells exposed to the conditioned medium of MDA-MB-231 cells silenced for HMGA1 and FOXM1 and in vivo injecting MDA-MB-231 cells, silenced for the two factors, in zebrafish larvae. Results Here, we discover FOXM1 as a novel molecular partner of HMGA1 in regulating a gene network implicated in several breast cancer hallmarks. HMGA1 forms a complex with FOXM1 and stabilizes it in the nucleus, increasing its transcriptional activity on common target genes, among them, VEGFA, the main inducer of angiogenesis. Furthermore, we demonstrate that HMGA1 and FOXM1 synergistically drive breast cancer cells to promote tumor angiogenesis both in vitro in endothelial cells and in vivo in a zebrafish xenograft model. Moreover, using a dataset of breast cancer patients we show that the co-expression of HMGA1, FOXM1 and VEGFA is a negative prognostic factor of distant metastasis-free survival and relapse-free survival. Conclusions This study reveals FOXM1 as a crucial interactor of HMGA1 and proves that their cooperative action supports breast cancer aggressiveness, by promoting tumor angiogenesis. Therefore, the possibility to target HMGA1/FOXM1 in combination should represent an attractive therapeutic option to counteract breast cancer angiogenesis

Oral and intestinal dysbiosis in Parkinson's disease.

The suspicion of an origin of Parkinson's disease (PD) at the periphery of the body and the involvement of environmental risk factors in the pathogenesis of PD have directed the attention of the scientific community towards the microbiota. The microbiota represents all the microorganisms residing both in and on a host. It plays an essential role in the physiological functioning of the host. In this article, we review the dysbiosis repeatedly demonstrated in PD and how it influences PD symptoms. Dysbiosis is associated with both motor and non-motor PD symptoms. In animal models, dysbiosis only promotes symptoms in individuals genetically susceptible to Parkinson's disease, suggesting that dysbiosis is a risk factor but not a cause of Parkinson's disease. We also review how dysbiosis contributes to the pathophysiology of PD. Dysbiosis induces numerous and complex metabolic changes, resulting in increased intestinal permeability, local and systemic inflammation, production of bacterial amyloid proteins that promote α-synuclein aggregation, as well as a decrease in short-chain fatty acid-producing bacteria that have anti-inflammatory and neuroprotective potential. In addition, we review how dysbiosis decreases the efficacy of dopaminergic treatments. We then discuss the interest of dysbiosis analysis as a biomarker of Parkinson's disease. Finally, we give an overview of how interventions modulating the gut microbiota such as dietary interventions, pro-biotics, intestinal decontamination and fecal microbiota transplantation could influence the course of PD

Caregiver Participation Engagement in Child Mental Health Prevention Programs: a Systematic Review

Prevention programs are a key method to reduce the prevalence and impact of mental health disorders in childhood and adolescence. Caregiver participation engagement (CPE), which includes caregiver participation in sessions as well as follow-through with homework plans, is theorized to be an important component in the effectiveness of these programs. This systematic review aims to (1) describe the terms used to operationalize CPE and the measurement of CPE in prevention programs, (2) identify factors associated with CPE, (3) examine associations between CPE and outcomes, and (4) explore the effects of strategies used to enhance CPE. Thirty-nine articles representing 27 unique projects were reviewed. Articles were included if they examined CPE in a program that focused to some extent on preventing child mental health disorders. There was heterogeneity in both the terms used to describe CPE and the measurement of CPE. The majority of projects focused on assessment of caregiver home practice. There were no clear findings regarding determinants of CPE. With regard to the impact of CPE on program outcomes, higher levels of CPE predicted greater improvements in child and caregiver outcomes, as well as caregiver-child relationship quality. Finally, a small number of studies found that motivational and behavioral strategies (e.g., reinforcement, appointment reminders) were successful in promoting CPE. This review highlights the importance of considering CPE when developing, testing, and implementing prevention programs for child mental health disorders. Increased uniformity is needed in the measurement of CPE to facilitate a better understanding of determinants of CPE. In addition, the field would benefit from further evaluating strategies to increase CPE as a method of increasing the potency of prevention programs

Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions

High-throughput molecular technologies can profile microbial communities at high resolution even in complex environments like the intestinal microbiota. Recent improvements in next-generation sequencing technologies allow for even finer resolution. We compared phylogenetic profiling of both longer (454 Titanium) sequence reads with shorter, but more numerous, paired-end reads (Illumina). For both approaches, we targeted six tandem combinations of 16S rRNA gene variable regions, in microbial DNA extracted from a human faecal sample, in order to investigate their limitations and potentials. In silico evaluations predicted that the V3/V4 and V4/V5 regions would provide the highest classification accuracies for both technologies. However, experimental sequencing of the V3/V4 region revealed significant amplification bias compared to the other regions, emphasising the necessity for experimental validation of primer pairs. The latest developments of 454 and Illumina technologies offered higher resolution compared to their previous versions, and showed relative consistency with each other. However, the majority of the Illumina reads could not be classified down to genus level due to their shorter length and higher error rates beyond 60 nt. Nonetheless, with improved quality and longer reads, the far greater coverage of Illumina promises unparalleled insights into highly diverse and complex environments such as the human gut

Risks, benefits, and knowledge gaps of non-native tree species in Europe

Changing ecosystem conditions and diverse socio-economical events have contributed to an ingrained presence of non-native tree species (NNTs) in the natural and cultural European landscapes. Recent research endeavors have focused on different aspects of NNTs such as legislation, benefits, and risks for forestry, emphasizing that large knowledge gaps remain. As an attempt to fulfill part of these gaps, within the PEN-CAFoRR COST Action (CA19128) network, we established an open-access questionnaire that allows both academic experts and practitioners to provide information regarding NNTs from 20 European countries. Then, we integrated the data originating from the questionnaire, related to the country-based assessment of both peer-reviewed and grey literature, with information from available datasets (EUFORGEN and EU-Forest), which gave the main structure to the study and led to a mixed approach review. Finally, our study provided important insights into the current state of knowledge regarding NNTs. In particular, we highlighted NNTs that have shown to be less commonly addressed in research, raising caution about those characterized by an invasive behavior and used for specific purposes (e.g., wood production, soil recultivation, afforestation, and reforestation). NNTs were especially explored in the context of resilient and adaptive forest management. Moreover, we emphasized the assisted and natural northward migration of NNTs as another underscored pressing issue, which needs to be addressed by joint efforts, especially in the context of the hybridization potential. This study represents an additional effort toward the knowledge enhancement of the NNTs situation in Europe, aiming for a continuously active common source deriving from interprofessional collaboration. Copyright © 2022 Dimitrova, Csilléry, Klisz, Lévesque, Heinrichs, Cailleret, Andivia, Madsen, Böhenius, Cvjetkovic, De Cuyper, de Dato, Ferus, Heinze, Ivetić, Köbölkuti, Lazarević, Lazdina, Maaten, Makovskis, Milovanović, Monteiro, Nonić, Place, Puchalka and Montagnoli