Background/Objective: Myopia has become a prominent public health issue in China, significantly impacting the visual health of children and adolescents. The condition is characterized by a high incidence rate, increasing prevalence, and a trend toward earlier onset, highlighting the critical need for early and accurate diagnosis. Current clinical diagnostic methods primarily depend on subjective evaluations by optometrists and the use of isolated parameters, leading to inefficiencies and inconsistent outcomes. Moreover, there remains a lack of diagnostic tools that can effectively integrate multi-parameter analysis while ensuring robust data privacy protection. This study aims to develop an artificial intelligence (AI) diagnostic model that achieves objective, accurate, and safe diagnosis of myopia in children without cycloplegia through multi-parameter fusion and to enable local deployment. The proposed model is intended to be a reliable tool for clinical applications and large-scale screening projects, while ensuring strong protection of patient privacy. Methods: We built a transparent, rule-driven AI framework using clinical guidelines. Key ocular parameters-visual acuity, spherical equivalent, axial length, corneal curvature, and axial ratio-were encoded as logical rules in Python and incorporated via instruction fine-tuning. The model was trained and validated on retrospective clinical data (70% training, 15% validation, 15% test) using five algorithms: gradient boosting, logistic regression, random forest, SVM, and XGBoost. Performance was evaluated using accuracy, precision, recall, F1 score, and mean AUC across classes. Results: The model classifies refractive status into five categories: hyperopia, pre-myopia, mild, moderate, and high myopia. All five different algorithms demonstrated excellent diagnostic and classification performance. Gradient boosting achieved the best overall performance, with an accuracy of 98.67%, an F1 score of 98.67%, and a mean AUC of 0.957-outperforming all other models. Conclusions: This study successfully developed an artificial intelligence-based myopia diagnosis system for children under non-dilated pupil conditions. The system is interpretable and privacy-preserving, and has excellent diagnostic and classification performance, making it suitable for clinical decision support and large-scale screening applications. It has great potential to promote the development of early intervention, precision prevention, and control strategies for childhood myopia.

We describe a unique case of combined baclofen and tizanidine overdose followed by dual withdrawal syndromes, highlighting overlapping and contrasting clinical features that may complicate diagnosis and management. A 26-year-old man with paraplegia from cervical spinal cord injury, prescribed baclofen and tizanidine for spasticity, was found unresponsive at home next to partially empty medication bottles. Clinical evaluation included laboratory testing, neuroimaging, continuous monitoring, and serial neurologic and cardiopulmonary assessments. On admission, the patient exhibited CNS depression, hypotension, bradycardia, hypothermia, and subsequent episodes of severe psychomotor agitation. Supportive care with fluids, vasopressors, and sedation was required, including 2 subsequent intubations for airway protection. Within 24 hours, fever, tachycardia, and worsening agitation developed, consistent with withdrawal. Reintroduction of home baclofen and tizanidine alongside benzodiazepines and dexmedetomidine led to gradual resolution of symptoms, and the patient was discharged at neurologic baseline with psychiatric follow-up. This case underscores the diagnostic and therapeutic challenges of overlapping baclofen and tizanidine toxicity and withdrawal. Recognizing key bedside features-such as hypotonia vs tremor and mydriasis vs miosis-is essential. Sedation and bradycardia may be more severe in combined overdose than in overdose of either agent alone. Clinicians should anticipate withdrawal even in the setting of persistent toxicity. Early recognition and tailored supportive care are the cornerstone of management.

Scopolamine, also known as hyoscine, is a naturally occurring tropane alkaloid derived from plants of the Solanaceae family. Clinically, the compound has long been used for the prevention of motion sickness and postoperative nausea and vomiting, as well as for ophthalmological procedures requiring mydriasis and cycloplegia. However, beyond these established indications, increasing attention has been directed toward its broader neuropharmacological actions. This narrative review aims to summarise current knowledge regarding the pharmacological properties of scopolamine, with particular emphasis on its mechanisms of action and emerging implications in neuroscience and neuropsychiatric disorders. Scopolamine acts as a non-selective antagonist of muscarinic receptor subtypes M1-M5, interfering with cholinergic neurotransmission. Experimental and clinical studies demonstrate that scopolamine induces transient cognitive impairment. This property has led to its widespread use as a pharmacological model of Alzheimer's disease, enabling investigation of cholinergic contributions to cognitive decline. More recently, several early clinical studies suggested that intravenous administration may produce rapid reductions in depressive symptoms, possibly through modulation of glutamatergic neurotransmission and activation of mTORC1-dependent synaptic plasticity pathways in the prefrontal cortex. Nevertheless, subsequent trials have yielded inconsistent results, and the therapeutic relevance of these findings remains uncertain. Current evidence indicates that scopolamine's neuropsychiatric effects likely arise from complex interactions between cholinergic, glutamatergic, and neurotrophic signalling systems. Taken together, scopolamine represents both a valuable experimental tool for studying cholinergic function and a mechanistic framework for the development of novel therapeutics targeting rapid neuroplastic processes in neuropsychiatric disorders.

Distal anterior cerebral artery (DACA) aneurysms are rare, representing a small fraction of intracranial vascular malformations. Their management is complex due to their deep interhemispheric location and often unfavorable morphology. We present an exceptionally rare case of a 56-year-old woman who suffered a rupture of a 5-mm A2-segment DACA aneurysm, leading to a unique combination of simultaneous bilateral frontal intraparenchymal hemorrhage and an acute subdural hematoma. This specific hemorrhagic pattern is significantly rarer than the typical subarachnoid hemorrhage and is often associated with high-pressure bleeding jets or arachnoid adhesions. The patient presented in a critical neurological state with rapidly progressing bilateral mydriasis. Following urgent decompressive craniectomy and microsurgical clipping, she achieved a favorable recovery. This case adds significant value to the literature by illustrating that DACA aneurysms should be considered in the differential diagnosis of nontraumatic bilateral frontal bleeding, and it demonstrates that even in the presence of severe multi-compartmental hemorrhage, prompt surgical intervention can lead to a positive long-term outcome.