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Background: Up to 13% of adolescents suffer from depressive disorders. Despite the high psychological burden, adolescents rarely decide to contact child and adolescent psychiatric services. To provide a low-barrier alternative, our long-term goal is to develop a chatbot for early identification of depressive symptoms. To test feasibility, we followed a two-step procedure, a) collection and linguistic analysis of psychiatric interviews with healthy adolescents and adolescents with depressive disorders and training of classifiers for detection of disorders from their answers in interviews, and b) generation of additional adolescent utterances via Chat GPT to improve the previously created model., Methods: For step a), we collected standardized interviews with 53 adolescents, n = 40 with and n = 13 without depressive disorders. The transcribed interviews comprised 4,077 question-answer-pairs, with which we predicted the clinical rating (depressive/non-depressive) with use of a feedforward neural network that received BERT (Bidirectional Encoder Representations from Transformers) vectors of interviewer questions and patient answers as input. For step b), we used the answers of all 53 interviews to instruct Chat GPT to generate new similar utterances., Results: In step a), the classifier based on BERT was able to discriminate answers by adolescents with and without depression with accuracies up to 97% and identified commonly used words and phrases. Evaluating the quality of utterances generated in step b), we found that prompt engineering for this task is difficult as Chat GPT performs poorly with long prompts and abstract descriptions of expectations on appropriate responses. The best approach was to cite original answers from the transcripts in order to optimally mimic the style of language used by patients and to find a practicable compromise between the length of prompts that Chat GPT can handle and the number of examples presented in order to minimize literal repetitions in Chat GPT's output., Conclusion: The results indicate that identifying linguistic patterns in adolescents' transcribed verbal responses is promising and that Chat GPT can be leveraged to generate a large dataset of interviews. The main benefit is that without any loss of validity the synthetic data are significantly easier to obtain than interview transcripts., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Jarvers, Ecker, Donabauer, Kampa, Weißenbacher, Schleicher, Kandsperger, Brunner and Ludwig.)

Despite the proven efficacy of pre-exposure prophylaxis (PrEP) in preventing HIV acquisition, PrEP is underutilized by sexual and gender minority young adults in the 13 states in the United States "South." In this paper, we describe the process we used to develop a digital campaign to promote awareness and engagement of sexual and gender minority young adults in the Louisiana Department of Health's TelePrEP Program and provide campaign performance metrics. In Phase 1, we conducted formative research that informed campaign development and strategy. In total, 109 sexual and gender minority young adults completed a survey of PrEP constructs (e.g., facilitators, barriers). We also conducted three, sequential focus groups to iteratively generate, revise and refine the digital material. In collaboration with our strategic marketing partner (SMP), we developed 3 different ads and 1 video ad to promote on web and mobile-in app display, as well as Facebook, Instagram, and YouTube. Phase 2 focused on campaign implementation and evaluation (e.g., number of impressions, user activities on LA TelePrEP landing page). In the first few weeks of the campaign, data from tracking pixels indicated minimal activities on the landing page. We paused to revamp the campaign. Our SMP determined that a more young adult-focused landing page could bolster engagement. We created a new landing page and reran the campaign for 33 days. We saw substantially more user activities on the new landing page (n = 382) compared to the LA TelePrEP landing page (n = 185). Overall, we had 730,665 impressions and 475 link clicks. By collaborating with our SMP, we effectively and efficiently translated our community-engaged formative research into relevant and engaging digital content. This pilot study is one of the first to demonstrate the importance of using tracking pixels to monitor real-time user data to optimize performance of a digital PrEP campaign., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ocasio et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Superficial siderosis of the central nervous system is a chronic condition characterized by hemosiderin deposition in the brain and spinal cord. It's diagnosed by brain MRI. It can be caused by low-grade extravasation of blood into the subarachnoid space of the brain. There are 2 types of superficial siderosis cortical and infratentorial. Although asymptomatic in many cases; Cerebellar-predominant siderosis, a subtype of infratentorial, can affect hearing, gait, and even muscles. In this report, we present a case of a 51-year old female with complaints of hearing loss, unsteadiness in his lower limb, and spastic paresis. During MRI neuroimaging, we noticed findings of hypointensity areas within the brainstem and cerebellum, probably due to hemosiderin deposition. Based on the MRI findings, the patient was diagnosed with superficial siderosis. The patient was started on deferiprone and followed for the consecutive 18 months. Moderate improvement of the hearing loss and ataxia was noted while no change in muscle force. However, the repetitive MRI did not reveal any changes compared to the previous one., (Published by Elsevier Inc. on behalf of University of Washington.)

Septo-optic dysplasia (SOD) is a rare congenital disorder occurring in only 1 in 10,000 live births. Initially it was described in 1941 by Reeves and further discussed by the French-Swiss neurologist de Morsier (1956) as the disease further addressed his name. SOD is a combination of triads of hypoplasia of the optic nerve, agenesis of midline brain structures, and hypoplasia of the hypothalamic-pituitary axis. The pathophysiology of this rare congenital anomaly is yet to be understood, with some hypotheses in order to establish the diagnosis. The management modality depends on the presentation of the disease and requires a multidisciplinary approach. While most SOD patients present with visual, neurological, or endocrine abnormalities, in our case the patient was diagnosed incidentally while following up after an episode of acute respiratory distress syndrome and sepsis. We aim to highlight the aspects of clinical presentation in a patient with SOD and the importance of a multimodality follow-up approach., (© 2022 The Authors. Published by Elsevier Inc. on behalf of University of Washington.)

Multi-voxel pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data is an emerging approach for probing the neural correlates of cognition. MVPA allows cognitive states to be modeled as distributed patterns of neural activity and classified according to stimulus conditions. In practice, building a robust, generalizable classification model can be challenging because the number of voxels (features) far exceeds the number of stimulus instances/data observations. To avoid model overfitting, there is a need to select informative voxels before building a classification model. In this paper, we propose a robust feature (voxel) selection framework using mutual information (MI) and partial least square regression (PLS) to establish an informativeness index for prioritizing selection of voxels based on the degree of their association to the experimental conditions. We evaluated the robustness of our proposed framework by assessing performance of standard classification algorithms, when combined with our feature selection approach, in a publicly-available fMRI dataset of object-level representation widely used to benchmark MVPA performance (Haxby, 2001). The computational results suggest that our feature selection framework based on MI and PLS drastically improves the classification accuracy relative to those previously reported in the literature. Our results also suggest that highly informative voxels may provide meaningful insight into the functional-anatomic relationship of brain activity and stimulus conditions.

The p53 pathway is a central mediator of the apoptotic response. ASPP2/(53BP2L) (apoptosis-stimulating protein of p53 2, also known as 53BP2L) enhances apoptosis through selective stimulation of p53 transactivation of proapoptotic target genes. Although the Rb/E2F pathway regulates ASPP2/(53BP2L) transcription, the complex mechanisms controlling ASPP2/(53BP2L) levels and function remain unknown. We now report that proteasomal degradation modulates ASPP2/(53BP2L) protein levels and apoptotic function. Treatment of cells with proteasomal inhibitors, including the clinically utilized proteasomal inhibitor bortezomib, increases ASPP2/(53BP2L) protein but not RNA levels. Likewise, anthracycline-based chemotherapy, which has multiple mechanisms of action, including proteasomal inhibition, increases ASPP2/(53BP2L) protein but not RNA levels. Proteasomal inhibition or anthracycline treatment increases ASPP2/(53BP2L) protein stability and half-life. Furthermore, the central region of the ASPP2/(53BP2L) protein is ubiquitinated as would be expected for a proteasomal substrate. More importantly, small interfering RNA knockdown of ASPP2/(53BP2L) levels attenuated bortezomib-induced apoptosis, and this effect was greater in wild-type p53 cells. Because elevated levels of ASPP2/(53BP2L) are proapoptotic, these results described an important new molecular mechanism that modulates the p53-ASPP2/(53BP2L) apoptotic pathway.