Chinese self-report version of biological rhythms interview for assessment in neuropsychiatry (C-BRIAN-SR) - psychometric properties and prospective follow-up in patients with non-seasonal depression.

This study examined the psychometric properties and longitudinal changes of the self-reporting Traditional Chinese version of Biological Rhythms Interview for Assessment in Neuropsychiatry (C-BRIAN-SR) among healthy controls (HC) and patients with major depressive episode (MDE). Eighty patients with a current MDE and 80 HC were recruited. Assessments were repeated after two weeks in HC, and upon the discharge of MDE patients to examine the prospective changes upon remission of depression. The C-BRIAN-SR score was significantly higher in the MDE than HC group. The concurrent validity was supported by a positive correlation between scores of C-BRIAN-SR, Insomnia Severity Index and the Hospital Anxiety Depression Scale. C-BRIAN-SR negatively correlated MEQ in the MDE group (r = .30, p = 0.009), suggesting higher rhythm disturbances were associated with a tendency toward eveningness. A moderate test-retest reliability was found (r = .61, p < 0.001). A cut-off of 38.5 distinguished MDE subjects from HC with 82.9% of sensitivity and 81.0% of specificity. C-BRIAN-SR score normalized in remitted MDE patients but remained higher in the non-remitted. The C-BRIAN-SR is a valid and reliable scale for measuring the biological rhythms and may assist in the screening of patients with MDE.

Moral Injury Post-COVID-19: More Than Military? A Theological Perspective.

The author of this article considers moral distress theologically, as a potential shattering of core sustaining belief systems, hope, securities, self-identities, and organizing principles of one's existence. Shattering of individual moral expectations can occur in both medical and military moral injury.

EEG-based emotion recognition systems; comprehensive study.

Emotion recognition technology through EEG signal analysis is currently a fundamental concept in artificial intelligence. This recognition has major practical implications in emotional health care, human-computer interaction, and so on. This paper provides a comprehensive study of different methods for extracting electroencephalography (EEG) features for emotion recognition from four different perspectives, including time domain features, frequency domain features, time-frequency features, and nonlinear features. We summarize the current pattern recognition methods adopted in most related works, and with the rapid development of deep learning (DL) attracting the attention of researchers in this field, we pay more attention to deep learning-based studies and analyse the characteristics, advantages, disadvantages, and applicable scenarios. Finally, the current challenges and future development directions in this field were summarized. This paper can help novice researchers in this field gain a systematic understanding of the current status of emotion recognition research based on EEG signals and provide ideas for subsequent related research.

The validity and reliability of the Chinese version of the biological rhythms interview of assessment in neuropsychiatry in the community: a large Chinese college student population.

Objective: To test the psychometric properties of the Chinese version of the biological rhythms interview of assessment in neuropsychiatry (C-BRIAN) in a group of young adults with and without depressive symptoms. Methods: Three hundred and seventy-eight university students were recruited as participants. Based on the scores from Center for Epidemiological Survey Depression Scale (CES-D), students were divided into the depressed group and healthy group. Explorative factor analysis was applied to assess the construct validity of the C-BRIAN. The Pittsburgh Sleep Quality Index (PSQI) and CES-D were compared with the C-BRIAN to test the convergent validity. The internal consistency of the C-BRIAN was also examined. Results: Three factors were extracted (activities, eating patterns, and sleep factors) explaining 63.9% of the total variance. The internal consistencies were very good with a coefficient of 0.94 (overall) and 0.89-0.91 for three factors. The domains of activities, eating patterns, and sleep were moderately correlated with PSQI (r=0.579) and CES-D (r=0.559) (ps<0.01). Conclusion: Our findings suggest that C-BRIAN has good validity and reliability which can be used to assess the biological rhythm in the young adult population with depressive symptoms. C-BRIAN would be a reliable tool to detect depressive symptoms for timely prevention and intervention in the community.

The relationship between anxiety symptoms and disturbances in biological rhythms in patients with depression.

BACKGROUND: Biological rhythms denote the cyclical patterns of life activities anchored to a 24-hour cycle. Research shows that depression exhibits disturbances in biological rhythms. Yet, the relationship between these biological rhythms and concomitant anxiety symptoms is insufficiently investigated in structured clinical assessments. METHODS: This multicenter study, carried out in four Chinese hospitals, comprehensively examined the relationship between anxiety and disruptions in biological rhythms among patients with depression. The study encompassed 218 patients diagnosed with depression and 205 matched healthy controls. The Chinese version of the Biological Rhythms Interview of Assessment in Neuropsychiatry was utilized to evaluate the participants' biological rhythms, focusing on four dimensions: sleep, activity, social, and diet. RESULTS: In patients with depression, there is a significant positive correlation between the severity of anxiety symptoms and the disturbances in biological rhythms. The severity of anxiety and depression, along with the quality of life, are independently associated with disruptions in biological rhythms. The mediation model reveals that anxiety symptoms mediate the relationship between depressive symptoms and biological rhythms. CONCLUSION: This research highlights the role of anxiety within the spectrum of depressive disorders and the associated disturbances in biological rhythms. Our findings shed light on potential pathways towards more targeted preventive strategies and therapeutic interventions for individuals battling depression and anxiety.

Exposure to hexafluoropropylene oxide trimer acid (HFPO-TA) impairs 5-HT metabolism by impacting the brain-gut axis in mice.

Hexafluoropropylene oxide trimer acid (HFPO-TA) has been found to cause hepatotoxicity, lipotoxicity, and cytotoxicity. However, the effects of HFPO-TA exposure on nervous system toxicity are still unclear. Here, six-week-old male C57BL/6J mice were treated with 2, 20, and 200 µg/L HFPO-TA for six weeks. The untargeted transcriptome analysis was employed to identify differentially expressed mRNAs in the tissue of mouse hippocampi. Then, the levels of neurotransmitters were detected by ELISA analysis in hippocampal and colonic tissues. Real-time quantitative PCR and western blotting analysis were performed to detect the expression of genes associated with modulation of serotonin (5-HT) metabolism and blood-brain barrier. HFPO-TA exposure reduced the mRNA and protein expression of several tight junction protein-coded genes, including Occludin, Claudin-1, and ZO-1, in mice hippocampi, indicating that the blood-brain barrier was disrupted. Moreover, HFPO-TA exposure elevated the expression of neuroinflammatory factors, including TNF-α, IL-6, IL-1ß, TGF-α, and TGF-ß. Analysis of hippocampal transcriptomics suggested that HFPO-TA exposure would impair 5-HT generation and metabolic pathways. In keeping with this prediction, our findings confirmed that the levels of several neurotransmitters, including tryptophan (TRP), 5-HT, 5-HTP, and 5-HIAA, were all impaired by HFPO-TA exposure in the serum, colon, and hippocampus, as was the colonic and hippocampal expression of TRP and 5-HT metabolism-related genes such as SERT, MAO-A, and IDO. These results suggest that HFPO-TA nervous system toxicity in mice may be partly modulated by the brain-gut axis and that HFPO-TA exposure may negatively impact human mental health.

Brian Collier (1940-2024).

Dr. Brian Collier, the former Editor-in-Chief of the Journal of Neurochemistry from 1996 to 2006, passed away January 4th, 2024. Brian's illustrious career spanned the fields of neurochemistry and pharmacology. He published his findings on mechanisms of acetylcholine synthesis and storage in the Journal of Neurochemistry, and his contributions remain landmarks in neurochemical research.

Therapeutic hypothermia can cause non-infective C-reactive protein elevating.

Objective: To analyze the relationship between therapeutic hypothermia (TH) and whole blood high-sensitivity C-reactive protein (hs-CRP) in neonates with hypoxic-ischemic encephalopathy (HIE). Method: Retrospective analysis was made on the clinical data of hospitalized infants diagnosed with asphyxia in our neonatal intensive care unit from January 2014 to June 2021. According to whether TH was performed, they were divided into two groups, the control group (missed the time in other hospitals and did not receive TH) and the treatment group (TH group). In their first ten days, analysis was made on the hs-CRP, white blood cell (WBC) count, neutrophil percentage, platelet count (PLT), and brain MRI. The correlation analysis was carried out based on the severity of brain injury displayed by the brain MRI and the time of hs-CRP elevation to summarize the relationship between TH and the time of hs-CRP elevation and the severity of HIE. Results: 83 infants were included, 28 in the control group and 55 in the TH group. After birth, 33 infants (60.0%) in the TH group and 2 patients (7.1%) in the control group had elevated hs-CRP, which was statistically significant (P < 0.05). The time window for CRP elevation after TH was 72-96 h after the end of treatment; The results of the brain MRI showed 23 in the TH group and 11in the control group with moderate and severe HIE. 21 infants (all in the TH group) had elevated hs-CRP. MRI showed that the number of infants with mild injury or regular infants whose hs-CRP raised in the TH group was 12, and the rate of hs-CRP elevation was 37.5%; in the control group, the rate was 11.8%. The difference was significant. TH can decrease PLT and WBC, but no significance in the two groups. Blood and sputum cultures were negative in all infants, and there were no signs of infection. Conclusions: TH can increase the blood hs-CRP of HIE neonates, and the probability of its occurrence is related to the severity of HIE. The heavier the HIE, the higher the risk of hs-CRP elevation after TH; The hs-CRP elevation has little to do with infection, and it doesn't recommend using antibiotics actively.

Structural brain network deviations predict recovery after traumatic brain injury.

OBJECTIVE: Traumatic brain injury results in diffuse axonal injury and the ensuing maladaptive alterations in network function are associated with incomplete recovery and persistent disability. Despite the importance of axonal injury as an endophenotype in TBI, there is no biomarker that can measure the aggregate and region-specific burden of axonal injury. Normative modeling is an emerging quantitative case-control technique that can capture region-specific and aggregate deviations in brain networks at the individual patient level. Our objective was to apply normative modeling in TBI to study deviations in brain networks after primarily complicated mild TBI and study its relationship with other validated measures of injury severity, burden of post-TBI symptoms, and functional impairment. METHOD: We analyzed 70 T1-weighted and diffusion-weighted MRIs longitudinally collected from 35 individuals with primarily complicated mild TBI during the subacute and chronic post-injury periods. Each individual underwent longitudinal blood sampling to characterize blood protein biomarkers of axonal and glial injury and assessment of post-injury recovery in the subacute and chronic periods. By comparing the MRI data of individual TBI participants with 35 uninjured controls, we estimated the longitudinal change in structural brain network deviations. We compared network deviation with independent measures of acute intracranial injury estimated from head CT and blood protein biomarkers. Using elastic net regression models, we identified brain regions in which deviations present in the subacute period predict chronic post-TBI symptoms and functional status. RESULTS: Post-injury structural network deviation was significantly higher than controls in both subacute and chronic periods, associated with an acute CT lesion and subacute blood levels of glial fibrillary acid protein (r = 0.5, p = 0.008) and neurofilament light (r = 0.41, p = 0.02). Longitudinal change in network deviation associated with change in functional outcome status (r = -0.51, p = 0.003) and post-concussive symptoms (BSI: r = 0.46, p = 0.03; RPQ: r = 0.46, p = 0.02). The brain regions where the node deviation index measured in the subacute period predicted chronic TBI symptoms and functional status corresponded to areas known to be susceptible to neurotrauma. CONCLUSION: Normative modeling can capture structural network deviations, which may be useful in estimating the aggregate and region-specific burden of network changes induced by TAI. If validated in larger studies, structural network deviation scores could be useful for enrichment of clinical trials of targeted TAI-directed therapies.

Supporting the Wound Healing Process-Curcumin, Resveratrol and Baicalin in In Vitro Wound Healing Studies.

The purpose of the investigation was to evaluate the effect of the selected bioflavonoids curcumin, resveratrol and baicalin on the wound healing process in an in vitro model. In the study, Balb3t3 and L929 cell lines were used. The first step was the evaluation of the cytotoxicity of the substances tested (MTT assay). Then, using the scratch test (ST), the influence of bioflavonoids on the healing process was evaluated in an in vitro model. The second stage of the work was a mathematical analysis of the results obtained. On the basis of experimental data, the parameters of the Brian and Cousens model were determined in order to determine the maximum value of the cellular and metabolic response that occurs for the examined range of concentrations of selected bioflavonoids. In the MTT assays, no cytotoxic effect of curcumin, resveratrol and baicalin was observed in selected concentrations, while in the ST tests for selected substances, a stimulatory effect was observed on the cell division rate regardless of the cell lines tested. The results obtained encourage further research on the use of substances of natural origin to support the wound healing process.

Reliability and validity of the Chinese version of the biological rhythms interview of assessment in neuropsychiatry in patients with major depressive disorder.

BACKGROUND: Although disturbances in biological rhythms are closely related to the onset of major depressive disorder (MDD), they are not commonly assessed in Chinese clinical practice. The Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN) has been used to evaluate disturbances in biological rhythms in MDD. We aimed to assess and confirm the reliability and validity of the Chinese version of the BRIAN (C-BRIAN) in patients with MDD. METHODS: A total of 120 patients with MDD and 40 age- and sex-matched controls were recruited consecutively. Reliability was estimated using Cronbach's alpha, the split-half coefficient, and the test-retest coefficient; test-retest reliability was assessed using Spearman's correlation coefficient. A confirmatory factor analysis was used to determine the construct validity of the scale. The Pittsburgh Sleep Quality Index (PSQI) and the Morningness-Eveningness Questionnaire (MEQ) were used to check concurrent validity by evaluating the correlation between the C-BRIAN, PSQI, and MEQ. RESULTS: The overall Cronbach's α value was 0.898, indicating good internal consistency. The Guttman split-half coefficient was 0.792, indicating good split-half reliability. Moreover, the test-retest reliability for both the total and individual item score was excellent. Confirmatory factor analysis revealed that construct validity was acceptable (χ2/df = 2.117, GFI = 0.80, AGFI = 0.87, CFI = 0.848, and RMSEA = 0.097). Furthermore, total BRIAN scores were found to be negatively correlated with MEQ (r = - 0.517, P < 0.001) and positively correlated with PSQI (r = 0.586, P < 0.001). In addition, patients with MDD had higher BRIAN scores than those in controls. CONCLUSIONS: This study revealed that the C-BRIAN scale has great validity and reliability in evaluating the disturbance of biological rhythms in patients with MDD.

Utilizing machine learning algorithms to predict subject genetic mutation class from in silico models of neuronal networks.

BACKGROUND: Epilepsy is the fourth-most common neurological disorder, affecting an estimated 50 million patients globally. Nearly 40% of patients have uncontrolled seizures yet incur 80% of the cost. Anti-epileptic drugs commonly result in resistance and reversion to uncontrolled drug-resistant epilepsy and are often associated with significant adverse effects. This has led to a trial-and-error system in which physicians spend months to years attempting to identify the optimal therapeutic approach. OBJECTIVE: To investigate the potential clinical utility from the context of optimal therapeutic prediction of characterizing cellular electrophysiology. It is well-established that genomic data alone can sometimes be predictive of effective therapeutic approach. Thus, to assess the predictive power of electrophysiological data, machine learning strategies are implemented to predict a subject's genetically defined class in an in silico model using brief electrophysiological recordings obtained from simulated neuronal networks. METHODS: A dynamic network of isogenic neurons is modeled in silico for 1-s for 228 dynamically modeled patients falling into one of three categories: healthy, general sodium channel gain of function, or inhibitory sodium channel loss of function. Data from previous studies investigating the electrophysiological and cellular properties of neurons in vitro are used to define the parameters governing said models. Ninety-two electrophysiological features defining the nature and consistency of network connectivity, activity, waveform shape, and complexity are extracted for each patient network and t-tests are used for feature selection for the following machine learning algorithms: Neural Network, Support Vector Machine, Gaussian Naïve Bayes Classifier, Decision Tree, and Gradient Boosting Decision Tree. Finally, their performance in accurately predicting which genetic category the subjects fall under is assessed. RESULTS: Several machine learning algorithms excel in using electrophysiological data from isogenic neurons to accurately predict genetic class with a Gaussian Naïve Bayes Classifier predicting healthy, gain of function, and overall, with the best accuracy, area under the curve, and F1. The Gradient Boosting Decision Tree performs the best for loss of function models indicated by the same metrics. CONCLUSIONS: It is possible for machine learning algorithms to use electrophysiological data to predict clinically valuable metrics such as optimal therapeutic approach, especially when combining several models.

Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian.

Developing intelligent neuromorphic solutions remains a challenging endeavor. It requires a solid conceptual understanding of the hardware's fundamental building blocks. Beyond this, accessible and user-friendly prototyping is crucial to speed up the design pipeline. We developed an open source Loihi emulator based on the neural network simulator Brian that can easily be incorporated into existing simulation workflows. We demonstrate errorless Loihi emulation in software for a single neuron and for a recurrently connected spiking neural network. On-chip learning is also reviewed and implemented, with reasonable discrepancy due to stochastic rounding. This work provides a coherent presentation of Loihi's computational unit and introduces a new, easy-to-use Loihi prototyping package with the aim to help streamline conceptualization and deployment of new algorithms.

Reliability and validity of the Arabic version of the biological rhythms interview of assessment in neuropsychiatry.

BACKGROUND: Disruptions in biological rhythm (BR) are considered a factor in the spread of many chronic diseases such as hypertension, diabetes, and depression. It has been shown that imbalance in BR disrupts the body's physiological timings; therefore, it is essential to have a tool for BR evaluation. METHODS: A cross-sectional study was conducted on a sample of 403 Jordanian participants (200 depressed people and 203 control groups). Classical test theory (CTT) was used to evaluate the psychometric properties of the Arabic version of BRIAN. We aimed to validate the Arabic version of Biological Rhythms Interview Assessment in Neuropsychiatry (BRIAN) by investigating its internal consistency and validity, assessing its factor structure, and exploring its relationships with depression and sleep disorders. RESULTS: The internal consistency (α) was 0.91. The concurrent validity was supported by the severity of depression and sleep disorders (r = 0.87, r = 0.83, p < 0.001). The BRIAN's ability to differentiate between depressed people and the control group supported its discriminant validity (t = 21.2, p = 0.001). With a sensitivity of 75 and a specificity of 95.57, BRIAN revealed good accuracy in distinguishing between depressed and non-depressed persons at cutoff 44. The exploratory factor analysis (EFA) and the confirmatory factor analysis (CFA) analyses supported its proposed three-factor solutions. CONCLUSIONS: The results demonstrated that the BRIAN-A has acceptable validity in detecting BR and could be useful in examining the impact of circadian disturbance on the Arabic population.

Primary cardiac synovial sarcoma presenting with brain metastases.

Primary cardiac synovial sarcoma is a very rare primary cardiac tumor that usually arises in the right side of the heart. Brain metastases in primary cardiac sarcomas are not uncommon. Because of the wild nature of these tumors, they usually have poor outcomes. This study describes a 29-year-old female who presented with blurred vision, headache, nausea, vomiting and brain lesions in the radiologic study. Incidentally, two-dimensional echocardiography revealed a left atrial lesion. The patient underwent emergency cardiac surgery to resect the left atrial mass that arose from the atrial free wall and pulmonary veins. The diagnosis of the lesion was primary synovial sarcoma in the histopathologic examination.

Tumors that usually arises in the right side of the heart are very rare. These tumors can spread to other parts like brain. Because of the wild nature of these tumors, they usually have poor results. This study describes a 29-year-old female who comes to the hospital with vision problems, headache, nausea, vomiting and brain masses in the imaging. In addition, there was a mass on the left side of her heart. The patient underwent emergency heart surgery to resect the mass that arose from the heart wall and lung veins. The nature of the lesion was primary synovial sarcoma in the pathologic examination.

Prevalence and Factors Associated With the Risk of Delayed Sleep-Wake Phase Disorder in Japanese Youth.

Background: Delayed sleep-wake phase disorder (DSWPD) is more prevalent among the younger generation. However, the prevalence of this disorder in Asia, particularly Japan, has not yet been elucidated. Furthermore, the impact of DSWPD morbidity on daytime functioning and factors associated with the presence of the disorder remain unclear. Methods: A web-based survey was conducted among youth aged 15-30 years. In total, 7,810 individuals completed the questionnaire. The questionnaire included items on sociodemographic variables as well as the Japanese version of the Biological Rhythms Interview of Assessment in Neuropsychiatry self-report (J-BRIAN-SR), which assesses the risk of DSWPD, sleep behaviors and possibly related lifestyle variables, productivity loss [WHO Health and Work Performance Questionnaire (HPQ)], and health-related quality of life (HRQOL). The risk of DSWPD was indicated by a J-BRIAN-SR score greater than or equal to 40 points and days of absence ≥4 days per month. After comparing these variables for participants at risk of DSWPD and those who were not, the factors associated with the risk of DSWPD were examined using logistic regression analysis, with sociodemographic and lifestyle variables as independent variables. Results: The overall prevalence of participants at risk DSWPDs was 4.3%. Compared with participants without DSWPD, those at risk of DSWPD presented significantly worse HPQ and HRQOL scores. The risk of DSWPD was positively associated with the presence of currently treated diseases, length of nighttime liquid crystal display (LCD) viewing, and being a high school/university students. It was negatively associated with habitual exercise. Conclusion: The risk of DSWPD seemed to be consistent with reports from Western countries, and individuals possibly affected by the disorder were thought to have deteriorated daytime functioning. In addition, lifestyle specific to youth, such as long-term LCD viewing at night and relatively loose social constraints, could be associated with the presence of DSWPD in this generation.

SGEResU-Net for brain tumor segmentation.

The precise segmentation of tumor regions plays a pivotal role in the diagnosis and treatment of brain tumors. However, due to the variable location, size, and shape of brain tumors, the automatic segmentation of brain tumors is a relatively challenging application. Recently, U-Net related methods, which largely improve the segmentation accuracy of brain tumors, have become the mainstream of this task. Following merits of the 3D U-Net architecture, this work constructs a novel 3D U-Net model called SGEResU-Net to segment brain tumors. SGEResU-Net simultaneously embeds residual blocks and spatial group-wise enhance (SGE) attention blocks into a single 3D U-Net architecture, in which SGE attention blocks are employed to enhance the feature learning of semantic regions and reduce possible noise and interference with almost no extra parameters. Besides, the self-ensemble module is also utilized to improve the segmentation accuracy of brain tumors. Evaluation experiments on the Brain Tumor Segmentation (BraTS) Challenge 2020 and 2021 benchmarks demonstrate the effectiveness of the proposed SGEResU-Net for this medical application. Moreover, it achieves DSC values of 83.31, 91.64 and 86.85%, as well as Hausdorff distances (95%) of 19.278, 5.945 and 7.567 for the enhancing tumor, whole tumor, and tumor core on BraTS 2021 dataset, respectively.

Lifetime physical activity is associated with gut bacteria and brain health in people with multiple sclerosis: Focus on physical activity intensity.

BACKGROUND: Physical activity can improve brain health in people with multiple sclerosis (PwMS). One of the underlying mechanisms can be the modulation of gut bacteria. The association of different intensity of physical activity in a lifetime; and brain volume, lesion volume, and number, and gut bacteria counts were investigated in the current study. METHODS: Forty-five PwMS were recruited, and magnetic resonance imagining was used to evaluate brain volume, lesion volume, and number. Also, stool samples were taken for evaluation faecalibacterium prausnitzii, akkermansia muciniphila, prevotella, and bacteroides count. Moreover, lifetime physical activity was assessed using the adapted version of the historical activity questionnaire. RESULTS: Data revealed a significant association of physical activity with brain volume (r = 0.41), lesion volume (r=-0.35), lesion number (r=-0.37), akkermansia muciniphila (r=-0.34), prevotella (r = 0.52) and bacteroides (r=-0.32) count (p<0.05). Moderate-intensity of physical activity was associated with brain volume (r = 0.33), lesion volume (r=-0.38), prevotella (r = 0.35) and bacteroides (r=-0.40) count (p<0.05). Moreover, vigorous-intensity of physical activity was associated with brain volume (r = 0.38), lesion number (r=-0.39), akkermansia muciniphila (r=-0.30) and prevotella (r = 0.56) count (p<0.05). CONCLUSION: Our results suggest that lifetime physical activity is associated with brain health and gut bacteria count in PwMS. Additionally, the heterogeneity of the association of the physical activity intensities with the studied variables indicates the importance of using different intensities of physical activity to greater benefit from physical activity.

Online Noninvasive Assessment of Human Brain Death by Near-Infrared Spectroscopy with Protocol of O2 Inspiration.

Brain death is the irreversible loss of all the functions of the brain and brainstem. Compared to traditional diagnostic methods of brain death, near-infrared spectroscopy (NIRS) is a noninvasive, objective, cost-effective, and safe way of assessment of brain death. Eighteen brain dead patients and 20 healthy subjects were studied by NIRS, with a multiple-phase protocol at varied fractions of inspired O2 (FIO2). We found that the changes in the concentration ratios of oxyhemoglobin to deoxyhemoglobin (Δ[HbO2]/Δ[Hb]) in the cerebral cortex of brain dead patients were significantly higher than those of healthy subjects, and its low-to-high FIO2 phase was most sensitive, with a recommended threshold in the range 1.40-1.50. Our study indicated that NIRS is a promising technology for assessing brain death. The success of this application potentially offers a supplementary technique for the assessment of brain death in real time in order to be able to promptly offer quality-assured donor organs.