Development of a miniaturized and modular probe for fNIRS instrument.

Functional near-infrared spectroscopy (fNIRS) is a non-invasive and promising method for continuously monitoring hemodynamic and metabolic changes in tissues. However, the existing fNIRS equipment uses optical fiber, which is bulky, expensive, and time-consuming. We present a miniaturized, modular, novel silicon photomultiplier (SiPM) detector and develop a fNIRS instrument aimed at investigating the cerebral hemodynamic response for patients with epilepsy. Light emitting probe is a circle with a diameter of 5 mm. Independent and modular light source and detector are more flexible in placement. The system can be expanded to high-density measurement with 16 light sources, 16 detectors, and 52 channels. The sampling rate of each channel is 25 Hz. Instrument performance was evaluated using brain tissue phantom and in vivo experiments. High signal-to-noise ratio (60 dB) in source detector separation (SDS) of 30 mm, good stability (0.1%), noise equivalent power (0.89 pW), and system drift (0.56%) were achieved in the phantom experiment. Forearm blood-flow occlusion experiments were performed on the forearm of three healthy volunteers to demonstrate the ability to track rapid hemodynamic changes. Breath holding experiments on the forehead of healthy volunteers demonstrated the system can well detect brain function activity. The computer software was developed to display the original light signal intensity and the concentration changes of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (HbR) in real time. This system paves the way for our further diagnosis of epilepsy.

Safety and efficiency of deep brain stimulation in the elderly patients with Parkinson's disease.

AIMS: Deep brain stimulation (DBS) is not routinely performed in elderly patients (≥75 years old) to date because of concerns about complications and decreased benefit. This study aimed to evaluate the safety and efficacy of DBS in elderly patients with Parkinson's disease. METHODS: A retrospective analysis was performed using data from 40 elderly patients from four centers who were treated with neurosurgical robot-assisted DBS between September 2016 and December 2021. These patients were followed up for a minimum period of 2 years, with a subgroup of nine patients followed up for 5-7 years. Patient demographic characteristics, surgical information, pre- and postoperative motor scores, non-motor scores, activities of daily living, and complications were retrospectively analyzed. RESULTS: The mean surgical procedure duration was 1.65 ± 0.24 h, with a mean electrode implantation duration of 1.10 ± 0.23 h and a mean pulse generator implantation duration of 0.55 ± 0.07 h. The mean pneumocephalus volume, electrode fusion error, and Tao's DBS surgery scale were 16.23 ± 12.81 cm3, 0.81 ± 0.23 mm, and 77.63 ± 8.08, respectively. One patient developed a skin infection, and the device was removed. The Unified Parkinson's disease rating scale, Unified Parkinson's disease rating scale of Part III, tremor, rigidity, bradykinesia, axial, and Barthel index for activities of daily living (ADL-Barthel) scores significantly improved at the 2-year follow-up (p < 0.05). The levodopa equivalent daily dose (LEDD) was significantly reduced at the 2-year follow-up (p < 0.05). However, the Montreal cognitive assessment, Hamilton depression scale, and Hamilton anxiety scale scores did not significantly change during the 2-year follow-up (p > 0.05). Additionally, in the subgroup with a 5-year follow-up, the motor symptoms, ADL-Barthel score, and cognitive function worsened over time compared to baseline. However, there was still an improvement in motor symptoms and ADL with DBS on-stimulation compared with the off-stimulation state. The LEDD increased 5 years after surgery compared to that at baseline. Eleven patients had passed away during follow-up, the mean survival time was 38.3 ± 17.3 months after surgery, and the mean age at the time of death was 81.2 (range 75-87) years. CONCLUSION: Robot-assisted DBS surgery for the elderly patients with Parkinson's disease is accurate and safe. Motor symptoms and ADL significantly improve and patients can benefit from long-term neuromodulation, which may decrease the risk of death.

Spatial attention can transfer to the contralateral hemisphere in neonatal stroke patients: a case report following hemispherectomy.

Patients suffer hemispatial neglect after stroke. However, whether the function of spatial attention is reorganized to the contralateral brain remains poorly understood. Here we present a case report of neonatal stroke to demonstrate the reorganization of spatial attention in the contralateral hemisphere using a series of tests including star cancellation task, line bisection test, the bells test, letter cancellation test, and drawing tests. The patient underwent right hemispherectomy for treatment of refractory epilepsy and did not have hemispatial neglect after surgery, supporting transfer of function prior to the operation. After analyzing the literature in this field, we proposed that the function of spatial attention may transfer to the contralateral side in childhood. Thus, this study sheds new light on the preserved function of spatial attention in neonatal stroke patients even when hemispherectomy is performed.

An Overview of EEG-based Machine Learning Methods in Seizure Prediction and Opportunities for Neurologists in this Field.

The unpredictability of epileptic seizures is one of the most problematic aspects of the field of epilepsy. Methods or devices capable of detecting seizures minutes before they occur may help prevent injury or even death and significantly improve the quality of life. Machine learning (ML) is an emerging technology that can markedly enhance algorithm performance by interpreting data. ML has gained increasing attention from medical researchers in recent years. Its epilepsy applications range from the localization of the epileptic region, predicting the medical or surgical outcome of epilepsy, and automated electroencephalography (EEG) analysis to seizure prediction. While ML has good prospects with regard to detecting epileptic seizures via EEG signals, many clinicians are still unfamiliar with this field. This work briefly summarizes the history and recent significant progress made in this field and clarifies the essential components of the automatic seizure detection system using ML methodologies for clinicians. This review also proposes how neurologists can actively contribute to ensure improvements in seizure prediction using EEG-based ML.

Functional Hemispherectomy for Adult Rasmussen Encephalitis: A Case Report and Literature Review.

Rasmussen encephalitis (RE) is a rare and severe brain disorder that is associated with unilateral hemispheric atrophy and manifests as severe refractory epilepsy, hemiplegia, defects of motor and speech functions, and cognitive impairment. Treatment of RE, especially in adult patients, is extremely challenging. Herein, we report the case of an adult patient with RE who was treated with a functional hemispherectomy and achieved a favorable prognosis. A 29-year-old woman presented with a 24-year history of epileptic seizures. Neurological examination showed hemiplegia, homonymous hemianopsia, and right muscular atrophy. Neuropsychological examination demonstrated cognitive disorders. Serial magnetic resonance imaging (MRI) and computed tomography (CT) scans showed progressive encephalatrophy in the left hemisphere and ventriculomegaly in the left lateral ventricle. The Wada test showed that the right hemisphere was dominant for language. A functional hemispherectomy was performed. Postoperatively, no antiepileptic drugs were administered, and the patient remained seizure-free without aggravation of hemiplegia. Over a 2-year follow-up, cognitive functions improved. In an adult patient with RE, a favorable prognosis was achieved after functional hemispherectomy. The safety and efficacy of functional hemispherectomy in patients with RE is highlighted.

Hemichorea associated with cavernous angioma and a small errhysis: A case report and literature review.

RATIONALE: Chorea is a movement disorder characterized by randomly appearing involuntary movements of the face, neck, limbs, or trunk. Hemichorea is unilateral, involving one side of the body. Hemichorea is commonly caused by non-ketotic hyperglycemia and/or cerebrovascular injury to the contralateral basal ganglia. PATIENT CONCERNS: Here, we report the case of a patient diagnosed with hemichorea who had diabetes, cavernous angioma, and a small intracranial errhysis. Routine testing showed the patient's blood glucose level was slightly higher than the normal range. INTERVENTIONS: The errhysis was too small to be treated. DIAGNOSES: Brain magnetic resonance imaging showed a cavernous angioma with a small errhysis in the right putamen. OUTCOMES: Hemichorea was completely resolved after 4 months. LESSONS: If diabetes is well controlled and imaging indicates brain lesions suggestive of a recent stroke, a diagnosis of post-stroke hemichorea should be considered.

Aphasic status epilepticus as the sole symptom of epilepsy: A case report and literature review.

Aphasia is a common symptom encountered by neurologists. However, the presence of aphasia as the sole manifestation of partial status epilepticus is rare. The present study reports a case of aphasic status epilepticus in a 27-year-old right-handed female who presented after the abrupt onset of aphasia, which had persisted for 1.5 days. The patient's medical history included head trauma followed by a craniectomy and cranioplasty. Computed tomography scans revealed a lesion in the patient's left parietal lobe, and an electroencephalogram showed a spike and slow wave pattern in the left hemisphere of the brain during aphasia. The patient's condition improved after the oral administration of oxcarbazepine daily. In the present study it was observed that EEGs were a simple method to diagnose aphasic seizures and therefore EEG recordings should be performed in all cases of unexplained aphasia. In addition, the present study reviewed previously reported cases of aphasic status epilepticus.

Subcutaneous metastasis after three surgeries for brain metastasis from lung cancer: A case report and review of the literature.

Lung cancer is a common malignancy that is frequently associated with distant subcutaneous metastasis. However, reports of subcutaneous metastasis of lung cancer after three surgeries for recurrent brain metastasis are scarce. The present study describes the case of a 49-year-old female patient who was admitted to our hospital with a cutaneous mass. The patient had a history of lung cancer and had undergone three surgeries for brain metastases. The subcutaneous mass was considered to be an implantation metastasis from the previous brain metastases. The cutaneous mass was grossly resected and histopathological examination revealed adenocarcinoma. This case highlights the need to perform a comprehensive analysis for suspected subcutaneous masses in lung cancer patients. Furthermore, pathological examination is crucial for accurate diagnosis and timely treatment.

Stabilization of fractional-order singular uncertain systems.

This paper focuses on the state and static output feedback stabilization for fractional-order singular (FOS) uncertain linear systems with the fractional commensurate order 0<α<1, respectively. The objective is to design suitable feedback controllers that guarantee the stability of resulting closed-loop control systems. First, the sufficient conditions for robust asymptotical stability of the closed-loop control systems are presented. Next, based on the matrix׳s singular value decomposition (SVD) and linear matrix inequality (LMI) technics, some new results in the form of LMI are developed to the state and static output feedback controller synthesis for the FOS systems. Finally, three numerical examples are given to illustrate the effectiveness of the proposed design methods.

Development of a LC-MS-MS Method for Quantification of Valtrate and Its Application to Pharmacokinetic Study.

A simple and selective liquid chromatography-tandem mass spectrometric method for determination of valtrate in rat plasma was developed in this study. Chromatographic separation was achieved on a Thermo BDS HYPERSIL C18 column using acetonitrile-water-formic acid (75 : 25 : 0.1, v/v/v) as mobile phase in an isocratic mode of elution at a flow rate of 300 µL/min. MS-MS detection was performed in a positive ion electrospray ionization mode with the ion transitions 445.2 → 219.2 for valtrate and 355.2 → 135.1 for internal standard (sesamin). The developed method exhibited a linear dynamic range over 5.65-1695 ng/mL for valtrate in rat plasma. The overall extraction recovery of valtrate from plasma was 86.13-88.32%. The intra- and inter-day accuracy and precision were within the pre-defined limits of ≤15% at all concentrations. The method was successfully applied to pharmacokinetic studies of valtrate in rats.

A novel algorithm for the precise calculation of the maximal information coefficient.

Measuring associations is an important scientific task. A novel measurement method maximal information coefficient (MIC) was proposed to identify a broad class of associations. As foreseen by its authors, MIC implementation algorithm ApproxMaxMI is not always convergent to real MIC values. An algorithm called SG (Simulated annealing and Genetic) was developed to facilitate the optimal calculation of MIC, and the convergence of SG was proved based on Markov theory. When run on fruit fly data set including 1,000,000 pairs of gene expression profiles, the mean squared difference between SG and the exhaustive algorithm is 0.00075499, compared with 0.1834 in the case of ApproxMaxMI. The software SGMIC and its manual are freely available at http://lxy.depart.hebust.edu.cn/SGMIC/SGMIC.htm.