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PubMed2005

Homosexuality and HIV/AIDS prevention: the challenge of transferring lessons learned from Western Europe to Central and Eastern European Countries.

In order to stem the rapidly growing HIV/AIDS epidemics in Eastern Europe a transfer of prevention know-how and experience from Western European countries is necessary. The success of such a transfer is contingent on addressing a number of challenging issues. Monolithic ideas of East/West difference need to give way to the growing empirical evidence which not only shows a tremendous diversity but also many similarities among the 51 countries within the WHO European region. These include similarities regarding sexual attitudes and HIV prevention needs. Western constructs such as a gay identity need to be de-emphasized however, when it comes to promoting human rights (and thus improving HIV prevention for men who have sex with men) in Central and Eastern Europe. In asking the question of what should be transferred from Western Europe to other countries, both the strengths and weaknesses of the last 20 years of prevention need to be considered. In terms of Western European research the strength lies in identifying the social structural causes of HIV transmission. In terms of practice, the successes of instituting country-level structures while also working within the gay community are to be emphasized. Short-comings are evident in terms of reaching men of lower socio-economic status, cultural minorities and sex workers. On such questions, the expertise of Europe as a whole is needed in order to find new answers.

Diffusion of Innovation↗
PubMed2005

Exploring the impact of instructional approaches on the learning and transfer of medication dosage calculation competency.

AIM: The ability of nurses to perform accurate drug dosage calculations has repercussions for patients' well-being. How best to assist nurses develop competency in this area is paramount. This paper presents findings of a study conducted with undergraduate nurses to determine the effect of three instructional approaches on the learning of this skill. METHOD: The quasi-experimental study exposed participants to one of three instructional approaches: integrative learning, computerised learning and a combination of integrative and computerised learning. Quantitative and qualitative approaches were used to explore differences in the instructional approaches and gain further understanding of the learning process. RESULTS: There was no statistical difference between the three instructional approaches on knowledge acquisition and transfer measures, other than measures for procedural knowledge, which was significant (F(2,47) = 3.33 at p < .044). A least-significant difference post hoc test (alpha = 0. 10) indicated computerised learning was significantly more effective in developing procedural knowledge. CONCLUSION: The provision of instructional strategies, which facilitate development of conditional knowledge and automaticity, is necessary for competency development in dosage calculations. Furthermore, the curriculum must incorporate authentic tasks and permit time to support competency attainment.

Analysis of Variance↗
PubMed1990

Analogical learning and transfer in language-impaired children.

In this study, the trial-by-trial acquisition procedures developed by Gholson, Eymard, Morgan, and Kamhi (1987) were used to examine analogical reasoning processes in school-age language-impaired (LI) children and normal age peers. Subjects were 16 LI and 16 normally developing children between the ages 6:4 and 8:9 years. Half of the subjects heard only verbal presentations of the problems, whereas the other half heard the verbal presentations while simultaneously viewing physical demonstrations of the problems. The LI children who heard only verbal presentations of the problems took significantly longer to acquire the problem solutions than the other LI children and the normal children in both conditions. There were no differences in children's performance on the transfer task. Theoretical and clinical implications of the findings are discussed.

Child↗
PubMed2023

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis.

Large single-cell RNA datasets have contributed to unprecedented biological insight. Often, these take the form of cell atlases and serve as a reference for automating cell labeling of newly sequenced samples. Yet, classification algorithms have lacked the capacity to accurately annotate cells, particularly in complex datasets. Here we present SIMS (Scalable, Interpretable Machine Learning for Single-Cell), an end-to-end data-efficient machine learning pipeline for discrete classification of single-cell data that can be applied to new datasets with minimal coding. We benchmarked SIMS against common single-cell label transfer tools and demonstrated that it performs as well or better than state of the art algorithms. We then use SIMS to classify cells in one of the most complex tissues: the brain. We show that SIMS classifies cells of the adult cerebral cortex and hippocampus at a remarkably high accuracy. This accuracy is maintained in trans-sample label transfers of the adult human cerebral cortex. We then apply SIMS to classify cells in the developing brain and demonstrate a high level of accuracy at predicting neuronal subtypes, even in periods of fate refinement, shedding light on genetic changes affecting specific cell types across development. Finally, we apply SIMS to single cell datasets of cortical organoids to predict cell identities and unveil genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. When cell types are obscured by stress signals, label transfer from primary tissue improves the accuracy of cortical organoid annotations, serving as a reliable ground truth. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Brain organoids↗
PubMed2006

Estimating transfer of learning for self-instructional packages across dental schools.

The most common topic of research in dental education is assessing the effectiveness of self-instructional units in various formats compared to lectures covering the same material. Generally, these studies are of high methodological quality and reveal mixed results or results slightly favoring self-instruction. All such studies, save one, have been conducted in the context of various single schools, thus confounding the effects of self-instructional format with factors particular to schools and their students. A reanalysis, using Cronbach's generalizability analysis, was performed on a study in the literature that was conducted at six schools and measured student aptitude. The reanalysis found that the largest source of variance on immediate post-test quizzes for knowledge following a three-hour unit on disturbances in tooth development was the school at which the study was conducted (24 percent), followed by student aptitude measured by DAT score (20 percent). Difference in format among lecture, booklet, and audiotape presentations accounted for 5 percent of the variance. This reanalysis demonstrated that statistically significant results from rigorous experimental designs can overrepresent what is revealed by such research. The context-specificity of educational innovations may be underestimated because few studies are replicated across schools. Studies conducted as single schools, regardless of their methodological rigor, fail to address issues associated with potential transfer of findings to other schools.

Analysis of Variance↗
PubMed1989

Video-task assessment of learning and memory in macaques (Macaca mulatta): effects of stimulus movement on performance.

Effects of stimulus movement on learning, transfer, matching, and short-term memory performance were assessed with 2 monkeys using a video-task paradigm in which the animals responded to computer-generated images by manipulating a joystick. Performance on tests of learning set, transfer index, matching to sample, and delayed matching to sample in the video-task paradigm was comparable to that obtained in previous investigations using the Wisconsin General Testing Apparatus. Additionally, learning, transfer, and matching were reliably and significantly better when the stimuli or discriminanda moved than when the stimuli were stationary. External manipulations such as stimulus movement may increase attention to the demands of a task, which in turn should increase the efficiency of learning. These findings have implications for the investigation of learning in other populations, as well as for the application of the video-task paradigm to comparative study.

Animals↗
PubMed1982

Memory and septo-hippocampal connections in rats.

Operated control rats and rats with small lesions in the medial septal region were tested for postoperative retention and transfer learning in a pulse-shaped elevated maze. Both maze problems were, in an empirical sense, spatial. Only when the rats worked on an alteration problem with start box reversals between sessions could the performance be characterized as depending on working memory. It was the working-memory conditions that sustained lesion-induced impairment on the tests of retention and transfer learning, and the lesion-induced behavioral impairment did not ameliorate during the four additional training sessions. Performance on problems that could be solved by reference-memory mechanisms was not impaired by the lesions. The small, but effective, lesions in the medial septal region were presumed to have severed a substantial number of connections comprising the major anterior input from the septum to the hippocampus but to have left intact much of the anterior hippocampal efferents. It is concluded that spatial cognitive mapping is crucially dependent on a basis capability for working memory which, in turn, depends on circuitry involving connections from septal region to hippocampus.

Animals↗
PubMed2004

Role of the cerebellum in implicit motor skill learning: a PET study.

To depict neural substrates of implicit motor learning, regional cerebral blood flow was measured using positron emission tomography (PET) in 13 volunteers in the rest condition and during performance of a unimanual two-ball rotation task. Subjects rotated two balls in a single hand; a slow rotation (0.5 Hz) was followed by two sessions requiring as rapid rotation as possible. The process was repeated four times by a single hand (Block 1) and then by the opposite hand (Block 2). One group of volunteers began with the right hand (n = 7), and the other with the left (n = 6). Performance was assessed by both quickness and efficiency of movements. The former was assessed with the maximum number of rotation per unit time, and the latter with the electromyographic activity under constant speed of the movement. Both showed learning transfer from the right hand to the left hand. Activation of cerebrum and cerebellum varied according to hand. Activation common to both hands occurred in the bilateral dorsal premotor cortex and parasagittal cerebellum, right inferior frontal gyms, left lateral cerebellum and thalamus, supplementary motor area, and cerebellar vermis. The left lateral cerebellum showed the most prominent activation on the first trial of the novel task, and hence may be related the early phase of learning, or "what to do" learning. Left parasagittal cerebellum activity diminished with training both in first and second blocks, correlating inversely with task performance. This region may therefore be involved in later learning or "how to do" learning. The activity of these regions was less prominent with prior training than without it. Thus the left cerebellar hemisphere may be related to learning transfer across hands.

Adult↗
PubMed2026

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans↗