Writing and science connections : integrated instruction and assessment

Learning to write is a daunting task for many young children. The purpose of this study was to examine the impact of a combined approach to writing instruction and assessment on the writing performance of students in two grade 3 classes. Five forms and traits of writing were purposefully connected during writing lessons while exhibiting links to the four strands of the grade 3 Ontario science curriculum. Students then had opportunities to engage in the writing process and to self-assess their compositions using either student-developed (experimental group/teacher-researcher's class) or teachercreated (control group/teacher-participant's class) rubrics. Paired samples t-tests revealed that both the experimental and control groups exhibited statistically significant growth from pretest to posttest on all five integrated writing units. Independent samples t-tests showed that the experimental group outperformed the control group on the persuasive + sentence fluency and procedure + word choice writing tasks. Pearson product-moment correlation r tests revealed significant correlations between the experimental group and the teacher-researcher on the recount + ideas and report + organization tasks, while students in the control group showed significant correlations with the teacher-researcher on the narrative + voice and procedure + word choice tasks. Significant correlations between the control group and the teacher-participant were evident on the persuasive + sentence fluency and procedure + word choice tasks. Qualitative analyses revealed five themes that highlighted how students' self-assessments and reflections can be used to guide teachers in their instructional decision making. These findings suggest that educators should adopt an integrated writing program in their classrooms, while working with students to create and utilize purposeful writing assessment tools

Treatment of competition between complete fusion and quasifission in collisions of heavy nuclei

A model of competition between complete fusion and quasifission channels in fusion of two massive nuclei is extended to include the influence of dissipative effects on the dynamics of nuclear fusion. By using the multidimensional Kramers-type stationary solution of the Fokker-Planck equation, the fusion rate through the inner fusion barrier in mass asymmetry is studied. Fusion probabilities in symmetric 90Zr+90Zr, 100Mo+100Mo, 110Pd+110Pd, 136Xe+136Xe, almost symmetric 86Kr+136Xe and 110Pd+136Xe reactions are calculated. An estimation of the fusion probabilities is given for asymmetrical 62Ni+208Pb, 70Zn+208Pb, 82Se+208Pb, and 48Ca+244Pu reactions used for the synthesis of new superheavy elements.Comment: 29 pages, LaTeX, including 7 postscript figures, to appear in Nucl. Phys.

Neurologic phenotype of Schimke immuno-osseous dysplasia and neurodevelopmental expression of SMARCAL1

Schimke immuno-osseous dysplasia (OMIM 242900) is an uncommon autosomal-recessive multisystem disease caused by mutations in SMARCAL1 (swi/snf-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a-like 1), a gene encoding a putative chromatin remodeling protein. Neurologic manifestations identified to date relate to enhanced atherosclerosis and cerebrovascular disease. Based on a clinical survey, we determined that half of Schimke immuno-osseous dysplasia patients have a small head circumference, and 15% have social, language, motor, or cognitive abnormalities. Postmortem examination of 2 Schimke immuno-osseous dysplasia patients showed low brain weights and subtle brain histologic abnormalities suggestive of perturbed neuron-glial migration such as heterotopia, irregular cortical thickness, incomplete gyral formation, and poor definition of cortical layers. We found that SMARCAL1 is highly expressed in the developing and adult mouse and human brain, including neural precursors and neuronal lineage cells. These observations suggest that SMARCAL1 deficiency may influence brain development and function in addition to its previously recognized effect on cerebral circulation

Analysis of the Fusion Hindrance in Mass-symmetric Heavy Ion Reactions

The fusion hindrance, which is also denominated by the term extra-push, is studied on mass-symmetric systems by the use of the liquid drop model with the two-center parameterization. Following the idea that the fusion hindrance exists only if the liquid drop barrier (saddle point) is located at the inner side of the contact point after overcoming the outer Coulomb barrier, the reactions in which two barriers are overlapped with each other are determined. It is shown that there are many systems where the fusion hindrance does not exist for the atomic number of projectile or target nucleus $Z\leq43$, while for $Z>43$, all of the mass-symmetric reactions are fusion-hindered.Comment: 6 pages, 4 figures. to be published in Sci. in China

Competition of fusion and quasi-fission in the reactions leading to production of the superheavy elements

The mechanism of fusion hindrance, an effect observed in the reactions of cold, warm and hot fusion leading to production of the superheavy elements, is investigated. A systematics of transfermium production cross sections is used to determine fusion probabilities. Mechanism of fusion hindrance is described as a competition of fusion and quasi-fission. Available evaporation residue cross sections in the superheavy region are reproduced satisfactorily. Analysis of the measured capture cross sections is performed and a sudden disappearance of the capture cross sections is observed at low fusion probabilities. A dependence of the fusion hindrance on the asymmetry of the projectile-target system is investigated using the available data. The most promising pathways for further experiments are suggested.Comment: 8 pages, 7 figures, talk presented at 7th International School-Seminar on Heavy-Ion Physics, May 27 - June 1, 2002, Dubna, Russi

Artificial intelligence for neurodegenerative experimental models

INTRODUCTION: Experimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials. METHODS: Here we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research. RESULTS: Considering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross-model reproducibility and translation to human biology, while sustaining biological interpretability. DISCUSSION: AI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data. Highlights: There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross-species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi-omics analysis with AI offers exciting future possibilities in drug discovery.</p

Advances in microfluidic in vitro systems for neurological disease modeling

Neurological disorders are the leading cause of disability and the second largest cause of death worldwide. Despite significant research efforts, neurology remains one of the most failure‐prone areas of drug development. The complexity of the human brain, boundaries to examining the brain directly in vivo, and the significant evolutionary gap between animal models and humans, all serve to hamper translational success. Recent advances in microfluidic in vitro models have provided new opportunities to study human cells with enhanced physiological relevance. The ability to precisely micro‐engineer cell‐scale architecture, tailoring form and function, has allowed for detailed dissection of cell biology using microphysiological systems (MPS) of varying complexities from single cell systems to “Organ‐on‐chip” models. Simplified neuronal networks have allowed for unique insights into neuronal transport and neurogenesis, while more complex 3D heterotypic cellular models such as neurovascular unit mimetics and “Organ‐on‐chip” systems have enabled new understanding of metabolic coupling and blood–brain barrier transport. These systems are now being developed beyond MPS toward disease specific micro‐pathophysiological systems, moving from “Organ‐on‐chip” to “Disease‐on‐chip.” This review gives an outline of current state of the art in microfluidic technologies for neurological disease research, discussing the challenges and limitations while highlighting the benefits and potential of integrating technologies. We provide examples of where such toolsets have enabled novel insights and how these technologies may empower future investigation into neurological diseases

Artificial intelligence for neurodegenerative experimental models

INTRODUCTION: Experimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials. METHODS: Here we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research. RESULTS: Considering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross-model reproducibility and translation to human biology, while sustaining biological interpretability. DISCUSSION: AI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data. HIGHLIGHTS: There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross-species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi-omics analysis with AI offers exciting future possibilities in drug discovery

In Vivo Fate Analysis Reveals the Multipotent and Self-Renewal Features of Embryonic AspM Expressing Cells

Radial Glia (RG) cells constitute the major population of neural progenitors of the mouse developing brain. These cells are located in the ventricular zone (VZ) of the cerebral cortex and during neurogenesis they support the generation of cortical neurons. Later on, during brain maturation, RG cells give raise to glial cells and supply the adult mouse brain of Neural Stem Cells (NSC). Here we used a novel transgenic mouse line expressing the CreERT2 under the control of AspM promoter to monitor the progeny of an early cohort of RG cells during neurogenesis and in the post natal brain. Long term fate mapping experiments demonstrated that AspM-expressing RG cells are multi-potent, as they can generate neurons, astrocytes and oligodendrocytes of the adult mouse brain. Furthermore, AspM descendants give also rise to proliferating progenitors in germinal niches of both developing and post natal brains. In the latter –i.e. the Sub Ventricular Zone- AspM descendants acquired several feature of neural stem cells, including the capability to generate neurospheres in vitro. We also performed the selective killing of these early progenitors by using a Nestin-GFPflox-TK allele. The forebrain specific loss of early AspM expressing cells caused the elimination of most of the proliferating cells of brain, a severe derangement of the ventricular zone architecture, and the impairment of the cortical lamination. We further demonstrated that AspM is expressed by proliferating cells of the adult mouse SVZ that can generate neuroblasts fated to become olfactory bulb neurons