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BackgroundThe Rey-Osterrieth Complex Figure Test (RCFT) is a neuropsychological test that is widely used to assess visual memory and visuoconstructional deficits in patients with cognitive impairment, including Alzheimer disease (AD). Patients with AD have an increased tendency for exhibiting extraordinary behaviors in the RCFT for selecting the drawing area, organizing the figure, and deciding the order of images, among other activities. However, the conventional scoring system based on pen and paper has a limited ability to reflect these detailed behaviors. ObjectiveThis study aims to establish a scoring system that addresses not only the spatial arrangement of the finished drawing but also the drawing process of patients with AD by using digital pen data. MethodsA digital pen and tablet were used to copy complex figures. The stroke patterns and kinetics of normal controls (NCs) and patients with early-onset AD (EOAD) and late-onset AD (LOAD) were analyzed by comparing the pen tip trajectory, spatial arrangement, and similarity of the finished drawings. ResultsPatients with AD copied the figure in a more fragmented way with a longer pause than NCs (EOAD: P=.045; LOAD: P=.01). Patients with AD showed an increased tendency to draw the figures closer toward the target image in comparison with the NCs (EOAD: P=.005; LOAD: P=.01) Patients with AD showed the lower accuracy than NCs (EOAD: P=.004; LOAD: P=.002). Patients with EOAD and LOAD showed similar but slightly different drawing behaviors, especially in space use and in the initial stage of drawing. ConclusionsThe digitalized complex figure test evaluated copying performance quantitatively and further elucidated the patients’ ongoing process during copying. We believe that this novel approach can be used as a digital biomarker of AD. In addition, the repeatability of the test will delineate the process of executive functions and constructional organization abilities with disease progression.

PurposeTo report a patient in whom a glaucomatous optic disc pit (ODP) disappeared spontaneously.ObservationsA 59-year-old Korean woman presented with primary open-angle glaucoma, an ODP, and deep superior cecocentral scotomas. She was treated with topical ocular hypotensive medications and followed. Twenty-eight months later, the superior cecocentral scotomas were not detectable with repeated visual field testing. With repeated optical coherence tomography (OCT), the ODP was narrower and shallower; partially filled with prelaminar tissue, there was an increase in the minimal rim width. At the final examination, the cecocentral scotomas reappeared, although prelaminar tissue continued to fill the ODP.Conclusions and importanceODP can disappear spontaneously in glaucomatous eyes under ocular hypotensive treatment. However, this is not always associated with sustained visual field improvement.

Background The relationship between human papillomavirus (HPV) and Bowen disease (BD) is not fully understood. Objectives To investigate the differences in HPV detection rates in BD samples across various body regions and analyse the expression patterns of p53, p16 and Ki-67 in relation to HPV presence. Methods Tissue samples from patients diagnosed with BD, confirmed through histopathology, were retrospectively collected. Next-generation sequencing was used for HPV DNA detection. Immunohistochemistry (IHC) for p16, p53 and Ki-67 was performed. Results Out of 109 patients with BD, 21 (19.3%) were HPV-positive. All identified types were α-HPVs, with HPV-16 being the most common. The HPV detection rate was significantly higher in the pelvic (9/13, 69%, P < 0.001) and digital (5/10, 50%, P = 0.02) areas compared with those in the other regions. HPV presence was significantly correlated with p53 negativity (P = 0.002), the p53 'non-overexpression' IHC pattern (P < 0.001) and p16–p53 immunostain pattern discordance (P < 0.001). Conversely, there was no notable association between HPV presence and p16 positivity, the p16 IHC pattern or Ki-67 expression. Conclusions Our findings suggest the oncogenic role of sexually transmitted and genito-digitally transmitted α-HPVs in the pathogenesis of BD in pelvic and digital regions. Graphical Abstract Open in new tab Download slide [ABSTRACT FROM AUTHOR]

Respiratory rate (RR) is a vital indicator for assessing the bodily functions and health status of patients. RR is a prominent parameter in the field of biomedical signal processing and is strongly associated with other vital signs such as blood pressure, heart rate, and heart rate variability. Various physiological signals, such as photoplethysmogram (PPG) signals, are used to extract respiratory information. RR is also estimated by detecting peak patterns and cycles in the signals through signal processing and deep-learning approaches. In this study, we propose an end-to-end RR estimation approach based on a third-generation artificial neural network model—spiking neural network. The proposed model employs PPG segments as inputs, and directly converts them into sequential spike events. This design aims to reduce information loss during the conversion of the input data into spike events. In addition, we use feedback-based integrate-and-fire neurons as the activation functions, which effectively transmit temporal information. The network is evaluated using the BIDMC respiratory dataset with three different window sizes (16, 32, and 64 s). The proposed model achieves mean absolute errors of 1.37 ± 0.04, 1.23 ± 0.03, and 1.15 ± 0.07 for the 16, 32, and 64 s window sizes, respectively. Furthermore, it demonstrates superior energy efficiency compared with other deep learning models. This study demonstrates the potential of the spiking neural networks for RR monitoring, offering a novel approach for RR estimation from the PPG signal. [ABSTRACT FROM AUTHOR]