Medical students require a strong foundation in normal histology. However, current trends in medical school curricula have diminished time devoted to histology. Thus, there is a need for more efficient methods of teaching histology. We have developed a novel software program (Novel Diagnostic Educational Resource; https://pcs-webtest0.pathology.washington.edu/academics/pattern/) that uses annotated whole slide images to teach normal histology. Whole slide images of a wide variety of tissues were annotated by a trainee and validated by an experienced pathologist. Still images were extracted and transferred to the Novel Diagnostic Educational Resource web application. In Novel Diagnostic Educational Resource, an image was displayed briefly and the user was forced to identify the tissue type. The display time changed inversely based on cumulative accuracy to challenge the user and maintain engagement. A total of 129 second-year medical students completed the 30-minute Novel Diagnostic Educational Resource module. Surveys showed an increase in confidence from premodule (0% extremely confident, 4% very, 47% somewhat, and 49% not) to postmodule (9% extremely confident, 57% very, 32% somewhat, and 2% not), < .0001. Accuracy increased from 72.6% pretest to 95.7% posttest, < .002. The effect size (Cohen = 2.30) was very large, where 0.2 is a small effect, 0.5 moderate, and 0.8 large. Ninety-six percent of students would recommend Novel Diagnostic Educational Resource to other medical students, and 98% would use Novel Diagnostic Educational Resource to further enhance their histology knowledge. Novel Diagnostic Educational Resource drastically improved medical student accuracy in classifying normal histology and improved confidence. Additional study is needed to determine knowledge retention, but Novel Diagnostic Educational Resource has great potential for efficient teaching of histology given the curriculum time constraints in medical education.
Four versions of the novel Moletest on-device signal-processing analysis software, delivered on a single-application iPadPro11, were evaluated in pigmented skin lesions of patients sent for biopsy comparing its results with the lesion histology. The primary objective was to demonstrate that the nomela test provided at least 95 ± 2% sensitivity for not-melanoma. Proprietary software recognised the lesion perimeter, rejecting images with uncertain border, and performed analysis using non-scalar metrics of the image within the perimeter.
Low-frequency non-syndromic hearing loss (LFNSHL) is a rare auditory disorder affecting frequencies ≤ 2000 Hz. To elucidate its genetic basis, we conducted whole-exome sequencing on nine Chinese families (31 affected individuals) with LFNSHL. Four heterozygous pathogenic variants, including two novel variants, were identified in common LFNSHL-related genes (WFS1, DIAPH1) and less common genes (TNC, EYA4), achieving a 44% genetic diagnosis rate.
Gastric cancer remains a leading cause of cancer-related mortality worldwide. The prognosis often depends on early detection and understanding the molecular mechanisms involved in its progression. Periodic tryptophan protein 1 (PWP1) has emerged as a novel diagnostic marker, potentially linked to gastric cancer progression.
Gastric cancer (GC) remains a prevalent and aggressive malignancy with a poor prognosis. This study aimed to identify diagnostic and prognostic biomarkers while exploring their potential functions in GC. A total of 598 upregulated and 506 downregulated genes were identified in GC patients.
Learning new categories is fundamental to cognition, occurring in daily life through various sensory modalities. However, it is not well known how acquiring new categories can modulate the brain networks. Resting-state functional connectivity is an effective method for detecting short-term brain alterations induced by various modality-based learning experiences.
