Abstract: Lead poisoning poses a significant health risk, particularly in the context of unregulated herbal medicines. This case report details the death of a 59-year-old woman who succumbed to complications from lead poisoning (cerebral edema and encephalopathy) following the use of an herbal cream to treat hemorrhoids. This incident highlights the dangers associated with unregulated herbal products, which can often be contaminated with harmful substances like heavy metals. Despite the perception that herbal remedies are safer and more affordable alternatives to conventional treatments, their natural appeal does not mitigate the risk of contamination. Many herbal plants can accumulate metals from their environment,exacerbating the risk of lead exposure. This case underscores the urgent need for stricter regulations and oversight in the herbal medicine industry to prevent such health hazards. Implementing stronger regulatory measures are essential to ensure that all medicinal and cosmetic products are free from harmful contaminants and to safeguard public health against the significant risks associated with lead poisoning.

Abstract: This study evaluated the effectiveness of face shields in protecting the eyes from splinters generated during standard kendo head strikes. A shinai was coated with red paint to simulate splinter dispersion and used to strike a kendo dummy. Results showed that the dummy equipped with a face shield exhibited no paint marks in the eye region, indicating effective protection. In contrast, the dummy without a face shield sustained direct impact to the left eye area. These findings demonstrate that face shields provide effective protection against potential eye injuries during kendo practice.

Keywords: — Kendo, eye injury, sports injury, eye protection, safety.

Abstract—Severe alcoholic hepatitis (AH) is classically a disease of middle-aged adults with years of heavy alcohol use, but in this case we demonstrate that even a young, relatively healthy 23-year-old can develop life-threatening AH after a short period of moderate alcohol consumption, particularly in the context of metabolic risk factors. This report details the clinical course, management, and recovery of a 23-year-old male survivor of childhood acute lymphoblastic leukemia (ALL) with obesity, nonalcoholic fatty liver disease (NAFLD), and prediabetes, who developed severe AH after only two years of social drinking. The case is contextualized within the current epidemiology, pathophysiology, and guideline recommendations, highlighting the synergistic hepatotoxicity of metabolic dysfunction and alcohol, and underscoring the need for vigilance and preventive counseling in at-risk young adults. This case underscores the need for targeted surveillance and preventive counseling in cancer survivors, who represent a growing population at risk for alcohol-related liver disease due to improved long-term survival. By identifying these individuals early and integrating multidisciplinary care, there is potential to prevent severe outcomes and reduce healthcare burden. Current ACG and AASLD guidelines provide limited direction for atypical populations such as young cancer survivors. Our case suggests an urgent need to expand guideline frameworks to inc…

Abstract: The emergence of large language models (LLMs) such as OpenAI’s ChatGPT and Google’s Gemini has opened new possibilities for their use in standardized test preparation. This study evaluates the performance of ChatGPT 4.0 and Gemini (both December 2024 versions) on an official AAMC full-length Medical College Admission Test (MCAT) practice exam. Using a standardized input protocol, we compared the models’ answers and calculated accuracy, MCAT section scores, and percentile rankings. ChatGPT outperformed Gemini, achieving a score of 522 (99th percentile) with an accuracy of 90.87%, compared to Gemini’s 518 (95th percentile) and 84.78% accuracy, with a statistically significant difference (p = 0.005). While these results highlight the educational potential of LLMs, they also raise important questions about the relevance of standardized testing in an era of increasingly accessible AI tools. Furthermore, although LLMs perform well on exams, their nonnegligible error rates caution against their use in clinical decision-making without human oversight. This study contributes to the growing discussion on how AI may transform medical education, assessment, and the future role of physicians.

Keywords: AI, MCAT, large language models, standardized exams, ChatGPT, Gemini

Abstract: Neurofeedback (NF) has been increasingly applied to post-traumatic stress disorder (PTSD); however, the neurophysiological mechanisms underlying its clinical effects remain incompletely understood. This case report describes EEG spectral changes observed during an 11-week course of NF training in a male patient in his 50s diagnosed with PTSD. A low-beta NF protocol was applied (15–18 Hz reward; 2–8 Hz and 22–36 Hz inhibition), and resting-state EEG was recorded during eyesopen resting state and eyes-closed resting state. Spectral analysis was performed using the maximum entropy method (MEM). Following the sixth NF session, a marked but transient increase in delta band power (1–4 Hz) was observed during the eyes-open resting state; this increase subsequently subsided and returned to baseline levels, suggesting a rebound phenomenon rather than a sustained training effect. In contrast, alpha band power (8–12 Hz) during the eyes-closed resting state showed a sustained increase over the course of training. Subjectively, a temporary worsening of symptoms coincided with the delta increase, followed by persistent improvements in sleep stability, disappearance of traumarelated dreams, and enhanced emotional regulation, which were corroborated by clinical evaluation. The transient delta increase was interpreted as a possible delta rebound phenomenon reflecting a transitional phase of NF-induced neural reorganization rather than drowsiness o…

Abstract: Recently, kilohertz-frequency pulse-train stimulation has attracted attention as a novel neuromodulation method, as an alternative to conventional electrical pulses delivered at repetition rates below 200 Hz. In this study, we propose a new stimulation paradigm in which kilohertz-frequency stimulation is applied not as the main stimulus that directly induces neuronal excitation, but as a priming stimulus applied prior to the main stimulus. Using physiological experiments and numerical simulations, we demonstrated that the cortical response to the main stimulus was partially suppressed by the priming stimulus. These findings suggest the potential of kilohertz-frequency stimulation as a new strategy for precise activation of neural circuits in cortical prostheses.

Keywords: Intracortical Neural prosthesis, Kilohertz-Frequency Microstimulation, Physiological Experiment, Biophysical Simulation, Neural Excitability

Abstract: Estimating mental fatigue levels during physical exertion is essential for ensuring safety and optimizing performance in sports and other high-demand environments. However, it remains challenging due to the overlapping physiological signals involved. This study examines the effectiveness of various wearable sensors, including ECG, PPG, and EEG, as well as eye trackers, in estimating mental fatigue levels under conditions of physical fatigue. Multimodal sensor data collected during controlled experiments that combined cognitive tasks with physical exercise were analyzed, with a focus on machine learning models for estimating mental fatigue levels on a 10-class scale. The results show that although EEG is the most accurate single sensor for estimating mental fatigue under physical fatigue, a combination of ECG and eye-tracking achieves higher accuracy (79.16%) with minimal error (MAE=0.52). This combination offers a balance between performance and wearability for practical applications.

Keywords: Fatigue Assessment, Mental Fatigue, Wearable Sensors.

Abstract: Robot-assisted partial nephrectomy (RAPN) is the standard treatment for localized renal tumors. However, identifying buried tumors and determining resection margins remain challenging. This paper describes a novel augmented reality (AR) surgical navigation system that we are currently developing for RAPNs. The system generates an intra-abdominal point cloud from a stereo endoscopic camera video within approximately 1 second. Point cloud matching is performed between the intraabdominal point cloud and the organ model of the patient created from preoperative computed tomography/magnetic resonance imaging images. We employ a two-stage matching approach: global matching using fast point feature histograms for initial alignment, followed by iterative closest point refinement for precise registration. The system successfully achieved registration with an root mean squared error of 1.546 mm for the clinical data testing. By overlaying these point clouds with the matching results, the system enables accurate and intuitive visualization of tumor locations and the positions of blood vessels and other critical structures, even when they are located inside or behind the organs. This AR navigation system has the potential to improve surgical precision, reduce positive margin rates, and preserve healthy renal tissue during RAPN.

Keywords: Surgical Support, Robot-Assisted Partial Nephrectomy, Augmented Realit…

Abstract: Previous clinical studies have shown that electrical pulse trains delivered into the visual cortex can evoke artificial visual sensations in individuals with acquired blindness, demonstrating the feasibility of intracortical visual prostheses. Our previous physiological experiments in mouse brain slices revealed that a single microstimulation pulse can drive synchronized neuronal action potentials in the vicinity of stimulating microelectrode tip, enabling temporal control of cortical activity using retinal spike-timing-based pulse sequences. In this study, we developed a linear–nonlinear cascade model to predict cortical responses to such neuromorphic stimulation, and confirmed its ability to reproduce key features of the observed neural dynamics.

Keywords: Visual Prosthesis, Intracortical Microstimulation, Neuromorphic Spike, Physiological Experiment, Model Prediction

Abstract—Reactive arthritis (ReA) is a sterile inflammatory arthritis typically triggered by gastrointestinal or genitourinary infections, with common pathogens including Chlamydia trachomatis and Salmonella. Though rare, urinary tract infections (UTIs) caused by Enterococcus faecalis can also trigger ReA. Diagnosis is clinical, established through a recent infection history and characteristic joint involvement. We present a 61-year-old female with a history of depression and ADHD, who was found in a state of self-neglect and diagnosed with failure to thrive. During hospitalization, she developed symptoms of a UTI, and urine culture grew Enterococcus faecalis. Patient’s symptoms subsequently evolved to include joint stiffness, ocular discharge, and nasal congestion, she was diagnosed with reactive arthritis, likely triggered by her prolonged UTI. The patient was treated and showed improvement throughout her admission. This case highlights the importance of considering reactive arthritis in patients with atypical infectious triggers such as Enterococcus faecalis UTI, especially in the context of prolonged catheterization and persistent infection. Early recognition and appropriate management can improve outcomes. Further research is needed to better characterize the spectrum of pathogens implicated in ReA and to optimize diagnostic and therapeutic strategies.