Blood Oxygen Level Research Articles

The relationships between hippocampal cerebrovascular reactivity, hippocampal volume, and episodic memory in healthy ageing

AbstractBackgroundCerebrovascular biomarkers such as cerebrovascular reactivity (CVR) have previously been associated with episodic memory. However, the relationship between memory and regional CVR within the hippocampus is not well studied. Moreover, whether this association is affected by hippocampal volume remains to be investigated. This study investigated the associations between hippocampal physiology, structure, and memory in ageing.MethodData from 104 participants (Age: Mean = 77±4.9 years) of the ongoing Oxford Heart and Brain Study was analysed for this study. CVR was assessed by a compensatory change in the blood oxygenation level dependent magnetic resonance imaging (MRI) signal in response to a 5% CO2 challenge, hippocampus volume was measured by structural MRI, and episodic memory was assessed with the Hopkins Verbal Learning Test Revised (HVLT‐R).ResultMean hippocampal CVR decreased with age (β = ‐0.004, p = 0.006). Mean hippocampal CVR was positively associated with mean hippocampal volume (β = 0.11, p = 0.010), and this association was driven by the left hippocampus after correcting for age and sex. Higher hippocampal CVR was also associated with better performance on the HVLT (β = 13.8, p = 0.035). This association was fully mediated by hippocampal volume, suggesting a path from cerebrovascular reactivity to episodic memory (Sobel’s z = 2.16, p = 0.030, see Figure 1).ConclusionThis study presents novel findings showing that hippocampal CVR was associated with episodic memory, and this association was mediated by hippocampal volume. This suggests a pathway by which impairments in hippocampal CVR are associated with worse episodic memory via smaller hippocampal volumes.

Posisi Head Up Dapat Meningkatkan Saturasi Oksigen Pada Pasien Stroke : Literature Review

Stroke is one of the most common diseases in society. One of the nursing management of critical stroke patients is head-up intervention. Objective: to identify whether the head-up position affects the increase in oxygen levels in stroke patients. Research Methods: This type of research is a Literature Review study. The research was conducted by entering the keywords Head Up Position, Oxygen Saturation, and Stroke in the database. Then articles were selected based on inclusion and exclusion criteria. The articles used are articles published in the last 5 years. Results: A number of eight articles said that the head-up position can increase oxygen saturation, whereas two articles said that head up had no effect on increasing oxygen saturation levels. Conclusion: Based on search results and article analysis, it was found that the concept of the head-up position can increase oxygen saturation in stroke patients and cannot be maintained. Suggestion: the concept of the head-up position can increase blood oxygen levels in stroke patients not to be maintained until there are further studies with stronger results

Asymmetric and symmetric dimethylarginine in high altitude pulmonary hypertension (HAPH) and high altitude pulmonary edema (HAPE)

Introduction: High altitude exposure may lead to high altitude pulmonary hypertension (HAPH) and high altitude pulmonary edema (HAPE). The pathophysiologic processes of both entities have been linked to decreased nitric oxide (NO) availability.Methods: We studied the effect of acute high altitude exposure on the plasma concentrations of asymmetric (ADMA) and symmetric dimethylarginine (SDMA), L-arginine, L-ornithine, and L-citrulline in two independent studies. We further investigated whether these biomarkers involved in NO metabolism were related to HAPH and HAPE, respectively. Fifty (study A) and thirteen (study B) non-acclimatized lowlanders were exposed to 4,559 m for 44 and 67 h, respectively. In contrast to study A, the participants in study B were characterized by a history of at least one episode of HAPE. Arterial blood gases and biomarker concentrations in venous plasma were assessed at low altitude (baseline) and repeatedly at high altitude. HAPE was diagnosed by chest radiography, and HAPH by measuring right ventricular to atrial pressure gradient (RVPG) with transthoracic echocardiography. AMS was evaluated with the Lake Louise Score (LLS) and the AMS-C score.Results: In both studies SDMA concentration significantly increased at high altitude. ADMA baseline concentrations were higher in individuals with HAPE susceptibility (study B) compared to those without (study A). However, upon high altitude exposure ADMA only increased in individuals without HAPE susceptibility, while there was no further increase in those with HAPE susceptibility. We observed an acute and transient decrease of L-ornithine and a more delayed but prolonged reduction of L-citrulline during high altitude exposure. In both studies SDMA positively correlated and L-ornithine negatively correlated with RVPG. ADMA was significantly associated with the occurrence of HAPE (study B). ADMA and SDMA were inversely correlated with alveolar PO2, while L-ornithine was inversely correlated with blood oxygenation and haemoglobin levels, respectively.Discussion: In non-acclimatized individuals ADMA and SDMA, two biomarkers decreasing endothelial NO production, increased after acute exposure to 4,559 m. The observed biomarker changes suggest that both NO synthesis and arginase pathways are involved in the pathophysiology of HAPH and HAPE.

Causal Analysis of Physiological Sleep Data Using Granger Causality and Score-Based Structure Learning

Understanding how the human body works during sleep and how this varies in the population is a task with significant implications for medicine. Polysomnographic studies, or sleep studies, are a common diagnostic method that produces a significant quantity of time-series sensor data. This study seeks to learn the causal structure from data from polysomnographic studies carried out on 600 adult volunteers in the United States. Two methods are used to learn the causal structure of these data: the well-established Granger causality and “DYNOTEARS”, a modern approach that uses continuous optimisation to learn dynamic Bayesian networks (DBNs). The results from the two methods are then compared. Both methods produce graphs that have a number of similarities, including the mutual causation between electrooculogram (EOG) and electroencephelogram (EEG) signals and between sleeping position and SpO2 (blood oxygen level). However, DYNOTEARS, unlike Granger causality, frequently finds a causal link to sleeping position from the other variables. Following the creation of these causal graphs, the relationship between the discovered causal structure and the characteristics of the participants is explored. It is found that there is an association between the waist size of a participant and whether a causal link is found between the electrocardiogram (ECG) measurement and the EOG and EEG measurements. It is concluded that a person’s body shape appears to impact the relationship between their heart and brain during sleep and that Granger causality and DYNOTEARS can produce differing results on real-world data.

Design of The WBAN in The Mobile Health Monitoring System

WBAN (Wireless Body Area Network) technology is used in this study to provide an integrated health monitoring platform. The device utilizes MLX90615 for measuring body temperature, a Blood Pressure Sensor for measuring blood pressure and pulse rate, and a MAX30102 Sensor for measuring blood oxygen and blood glucose levels. The output of this utility is displayed on an OLED screen and is controlled by the NODEMCU ESP8266. The test reveals an accuracy of 94.8%, indicating that the instrument can provide accurate results and has a relatively low error rate on each sensor. Heart Rate Error on Blood Pressure Sensor 0; Spo2 Error on MAX 30102 Sensor 1; and Blood Sugar Error on MAX 30102 Sensor 2.0. Real-time health monitoring that is more accurate and efficient. This device has the potential to be a practical solution for routine health monitoring and provides significant benefits for maintaining health.

The impact of the new acute respiratory distress syndrome (ARDS) criteria on Berlin criteria ARDS patients: a multicenter cohort study

ObjectiveThe European Society of Intensive Care Medicine (ESICM) recently recommended changes to the criteria of acute respiratory distress syndrome (ARDS), patients with high-flow oxygen were included, however, the effect of these changes remains unclear. Our objectives were to evaluate the performance of these new criteria and to compare the outcomes of patients meeting the new ARDS criteria with those meeting the Berlin ARDS criteria.MethodsThis was a retrospective cohort. The patients admitted to the intensive care unit (ICU) were diagnosed with ARDS. Patients were classified as meeting Berlin criteria ARDS (n = 4279), high-flow nasal oxygen (HFNO) criteria ARDS (n = 559), or new criteria ARDS (n = 4838).ResultsIn comparison with HFNO criteria ARDS and new criteria ARDS, patients with Berlin criteria ARDS demonstrated lower blood oxygen levels assessed by PaO2/FiO2, SpO2/FiO2, and ROX (SpO2/FiO2/respiratory rate) (p < 0.001); and higher severity of illness assessed by the Sequential Organ Failure Assessment (SOFA) score, Acute Physiology And Chronic Health Evaluations (APACHE II), Simplified Acute Physiology Score (SAPS II) (p < 0.001), (p < 0.001), and longer ICU and hospital stays (p < 0.001). In comparison with the HFNO criteria, patients meeting Berlin criteria ARDS had higher hospital mortality (10.6% vs. 16.9%; p = 0.0082), 28-day mortality (10.6% vs. 16.5%; p = 0.0079), and 90-day mortality (10.7% vs. 17.1%; p = 0.0083). ARDS patients with HFNO did not have severe ARDS; Berlin criteria ARDS patients with severe ARDS had the highest mortality rate (approximately 33%). PaO2/FiO2, SpO2/FiO2, and ROX negatively correlated with the SOFA and APACHE II scores. The SOFA and APACHE II scores had high specificity and sensitivity for prognosis in patients with new criteria ARDS.ConclusionThe new criteria of ARDS reduced the severity of illness, length of stay in the ICU, length of hospital stays, and overall mortality. SOFA and APACHE II scores remain important in assessing the prognosis of patients with new criteria ARDS.Trial registrationRegistration number: ChiCTR2200067084.

IoT System for Monitoring of Workers at Height

Work at height is considered a high-risk task due to the exposure of personnel to non-daily or natural factors for the human being, such as changes in temperature, position and limited displacement, which might affect the person’s metabolism. In Colombia, over the years, this activity has represented a significant number of accidents and deaths. In order to be able to detect a possible eventuality or issue with the worker at height, this project proposed and developed an IoT prototype system to monitor biological variables, such as, heart rate and blood oxygen level, and variables of protection for the worker, such as the securing of the carabiner on the line of life and the height at which the worker is positioned. In the materials and methods section, the system architecture and its connections are explained. To measure heart rate and blood oxygen level, the plethysmography technique is selected, a high-resolution barometer is selected to measure the worker's height, and a pressure sensor is selected to measure carabiner securing. This section also explains the development of electronic instrumentation and the connection of the different modules to guarantee the acquisition of information and its sending to the cloud. The results of the characterization of the prototype indicated errors of 3.56% for the heart rate, 1.1% for the blood oxygen level and 10% for the carabiner securing measurement. As a conclusion the IoT system was designed, implemented and verified for the proposed variables. The system allows real-time measurements and connectivity between physical variables and the cloud.

Characterizing systemic physiological effects on the blood oxygen level dependent signal of resting-state fMRI in time-frequency space using wavelets.

Systemic physiological dynamics, such as heart rate variability (HRV) and respiration volume per time (RVT), are known to account for significant variance in the blood oxygen level dependent (BOLD) signal of resting-state functional magnetic resonance imaging (rsfMRI). However, synchrony between these cardiorespiratory changes and the BOLD signal could be due to neuronal (i.e., autonomic activity inducing changes in heart rate and respiration) or vascular (i.e., cardiorespiratory activity facilitating hemodynamic changes and thus the BOLD signal) effects and the contributions of these effects may differ spatially, temporally, and spectrally. In this study, we characterize these brain-body dynamics using a wavelet analysis in rapidly sampled rsfMRI data with simultaneous pulse oximetry and respiratory monitoring of the Human Connectome Project. Our time-frequency analysis across resting-state networks (RSNs) revealed differences in the coherence of the BOLD signal and heartbeat interval (HBI)/RVT dynamics across frequencies, with unique profiles per network. Somatomotor (SMN), visual (VN), and salience (VAN) networks demonstrated the greatest synchrony with both systemic physiological signals when compared to other networks; however, significant coherence was observed in all RSNs regardless of direct autonomic involvement. Our phase analysis revealed distinct frequency profiles of percentage of time with significant coherence between BOLD and systemic physiological signals for different phase offsets across RSNs, suggesting that the phase offset and temporal order of signals varies by frequency. Lastly, our analysis of temporal variability of coherence provides insight on potential influence of autonomic state on brain-body communication. Overall, the novel wavelet analysis enables an efficient characterization of the dynamic relationship between cardiorespiratory activity and the BOLD signal in spatial, temporal, and spectral dimensions to inform our understanding of autonomic states and improve our interpretation of the BOLD signal.

On a framework of data assimilation for hyperparameter estimation of spiking neuronal networks

When handling real-world data modeled by a complex network dynamical system, the number of the parameters is often much more than the size of the data. Therefore, in many cases, it is impossible to estimate these parameters and the exact value of each parameter is frequently less interesting than the distribution of the parameters. In this paper, we aim to estimate the distribution of the parameters in the mesoscopic neuronal network model from the macroscopic experimental data, for example, the BOLD (blood oxygen level dependent) signal. Herein, we assume that the parameters of the neurons and synapses are inhomogeneous but independently and identically distributed from certain distributions with unknown hyperparameters. Thus, we estimate these hyperparameters of the distributions of the parameters, instead of estimating the parameters themselves. We formulate this problem under the framework of data assimilation and hierarchical Bayesian method and present an efficient method named Hierarchical Data Assimilation (HDA) to conduct the statistical inference on the neuronal network model with the BOLD signal data simulated by the hemodynamic model. We consider the Leaky Integral-Fire (LIF) neuronal networks with four synapses and show that the proposed algorithm can estimate the BOLD signals and the hyperparameters with high preciseness. In addition, we discuss the influence on the performance of the algorithm configuration and the LIF network model setup.

Multimodal graph attention network for COVID-19 outcome prediction

When dealing with a newly emerging disease such as COVID-19, the impact of patient- and disease-specific factors (e.g., body weight or known co-morbidities) on the immediate course of the disease is largely unknown. An accurate prediction of the most likely individual disease progression can improve the planning of limited resources and finding the optimal treatment for patients. In the case of COVID-19, the need for intensive care unit (ICU) admission of pneumonia patients can often only be determined on short notice by acute indicators such as vital signs (e.g., breathing rate, blood oxygen levels), whereas statistical analysis and decision support systems that integrate all of the available data could enable an earlier prognosis. To this end, we propose a holistic, multimodal graph-based approach combining imaging and non-imaging information. Specifically, we introduce a multimodal similarity metric to build a population graph that shows a clustering of patients. For each patient in the graph, we extract radiomic features from a segmentation network that also serves as a latent image feature encoder. Together with clinical patient data like vital signs, demographics, and lab results, these modalities are combined into a multimodal representation of each patient. This feature extraction is trained end-to-end with an image-based Graph Attention Network to process the population graph and predict the COVID-19 patient outcomes: admission to ICU, need for ventilation, and mortality. To combine multiple modalities, radiomic features are extracted from chest CTs using a segmentation neural network. Results on a dataset collected in Klinikum rechts der Isar in Munich, Germany and the publicly available iCTCF dataset show that our approach outperforms single modality and non-graph baselines. Moreover, our clustering and graph attention increases understanding of the patient relationships within the population graph and provides insight into the network’s decision-making process.

Prone Positioning of Ventilated Patients During Air Medical Evacuation: A Case Series

ObjectiveThe purpose of this study was to investigate patient safety implications of transporting prone-positioned mechanically ventilated patients in the air medical environment (AME). MethodsA retrospective health record review of patient encounters from 2019 to 2021 was conducted using British Columbia Emergency Health Services air medical electronic patient care reports. ResultsA total of 633 patients were identified as intubated, mechanically ventilated, and transported by British Columbia Emergency Health Services air medical teams. Ten patients were identified as having been transported in the prone position. Oxygen saturation, arterial blood oxygen levels, and carbon dioxide measurements from 8 cases indicated that patients remained stable or improved during transport. Cardiovascular episodes including hypotension and tachycardia were observed. In 2 patients, a mean 17.5% decline in oxygen saturation was identified. It could not be determined if this was a result of prone positioning during AME or due to a deteriorating physiological condition related to the patient's underlying disease. There were no identified tube dislodgments during AME transport. ConclusionAlthough proning did not compromise patient safety with respect to tube or line displacement in our study, we cannot draw definitive conclusions regarding the safety implications of proning on patient vital signs during transport.

Structural and Physiological Modeling (SAPM) for the Analysis of Functional MRI Data Applied to a Study of Human Nociceptive Processing.

A novel method has been developed for analyzing connectivity between regions based on functional magnetic resonance imaging (fMRI) data. This method, termed structural and physiological modeling (SAPM), combines information about blood oxygenation-level dependent (BOLD) responses, anatomy, and physiology to model coordinated signaling across networks of regions, including input and output signaling from each region and whether signaling is predominantly inhibitory or excitatory. The present study builds on a prior proof-of-concept demonstration of the SAPM method by providing evidence for the choice of network model and anatomical sub-regions, demonstrating the reproducibility of the results and identifying statistical thresholds needed to infer significance. The method is further validated by applying it to investigate human nociceptive processing in the brainstem and spinal cord and comparing the results to the known neuroanatomy, including anatomical regions and inhibitory and excitatory signaling. The results of this analysis demonstrate that it is possible to obtain reliable information about input and output signaling from anatomical regions and to identify whether this signaling has predominantly inhibitory or excitatory effects. SAPM provides much more detailed information about neuroanatomy than was previously possible based on fMRI data.

Heart Rate Monitoring, Blood Oxygen Levels and Location Determination for Covid 19 Patients Using Internet of Things Technology

The COVID-19 virus is very dangerous. In addition to attacking the lungs, this virus can also attack the heart directly. The relationship between heart health and COVID-19 occurs because blood vessel clots in COVID-19 patients increase the risk of blood vessel disorders and make the heart work harder. Therefore, researchers designed a heart rate monitoring device. This tool serves to maintain heart health and oxygen levels in the patient's blood and can also monitor people under COVID surveillance. The formulation of the problem from this research is how to design an IoT system to monitor COVID-19 patients through heart rate and location and how it performs. The purpose of this study is to analyze the performance of the device and design a tool to measure heart rate and blood oxygen levels through the IoT system and GPS location so that doctors can access heart rate data from any location. This research method uses a Gy-MAX30100 sensor, Wemos, and a GPS module. Of the 2 data samples that have been tested, the highest heart rate value is 78 bpm, the lowest is 76 bpm, and the highest oxygen level is 95 mmHg and the lowest is 93 mmHg. So in conclusion, this tool can make it easier for doctors to get important information about the condition of patients or people under observation that can be accessed by doctors anywhere and anytime via the internet.

Abstract 15900: Probing Mitochondrial Dysfunction in Mouse Hearts With Doxorubicin-Induced Cardiotoxicity Using Ungated 4D Oxy-Wavelet MRI

Introduction: Despite advances in cancer therapy greatly improving patient survival, more than two-thirds of cancer survivors will still face serious life-threatening cardiomyopathy caused by anti-cancer anthracyclines. Doxorubicin (Dox), a well-known, well studied anthracycline, is a major cause for long-term morbidity and mortality among cancer survivors. Pertinent to this issue is the lack of non-invasive imaging tools that can detect DOX induced cardiomyopathy before irreversible tissue damage is done. Current research of cellular mechanisms underlying DOX-induced cardiotoxicity has shown that mitochondrial dysfunction are central to this cardiomyopathy. Hypothesis: We hypothesize that this mitochondrial dysfunction precedes clinical changes in cardiac strain and left-ventricle ejection fraction. Methods: To probe mitochondrial function non-invasively, we use motion-and-time resolved 4D functional MRI, coined 4D Oxy-Wavelet. Our methodology can capture dynamic changes in the blood oxygenation level dependent (BOLD) signal with high spatiotemporal resolution. Our cyclic hypoxia challenge leverages the need for in-tact mitochondrial function to maintain homeostatic oxygenation during hypoxia. We combine our 4D-fMRI methodology with a cyclic hypoxia challenge to stress-test the mitochondria in a mouse model of DOX-induced cardiotoxicity. We use a novel time-frequency analysis of the event-driven BOLD response to automate the detection of mitochondrial dysfunction in-vivo. Results: C57BL6/J were given Dox over the course of one week. 4D oxy-wavelet MRI was performed at baseline, day 1, 3, 4, and 7 to evaluate the ability to rapidly detect acute DOX induced cardiotoxicity. We found that as early as day one post exposure, mice exhibited a passive response to the hypoxia challenge, representing an inability to maintain homeostatic oxygen and underlying mitochondria dysfunction, that was maintained through this acute period.

Abstract 11433: Elevated Vascular Endothelial Growth Factor A is Associated With Disruption of Default Network Connectivity

Introduction: Vascular Endothelial Growth Factor A (VEGF-A) is an angiogenic signaling protein involved in the maintenance of the cerebral vasculature. VEGF-A may play a role in the pathogenesis of Alzheimer’s disease and vascular dementia; however, whether elevated VEGF-A levels indicate a pathophysiolocal response or protective mechanism remains unclear. No prior study has explored whether VEGF-A levels may be associated with changes in functional connectivity among brain regions prior to the development of cognitive decline. Hypothesis: Disruption of the default network often precedes the development of cognitive changes. In a sample of older adults, we hypothesized that VEGF-A levels may be associated with default network connectivity, indicating early involvement of VEGF-A in disease processes. Methods: Forty-six independently living older adults (mean age = 72.0 years; SD = 6.4; 34.8% male) free of dementia or clinical stroke underwent venipuncture and brain MRI. Plasma was assayed for VEGF-A. Using resting state functional MRI, blood-oxygen level dependent (BOLD) time series from all voxels in each region of interest (ROI) was averaged to determine mean ROI activity. Medial prefrontal cortex, lateral parietal cortex and precuneus cortex ROIs comprised the default network. Results: Accounting for age and sex, multiple linear regression analysis revealed a significant negative association between VEGF-A levels and default mode network connectivity (B =-.0007, 95% CI (-.0012, -.0002), p = .0096). This association persisted after adjusting for APOE4 carrier status and Framingham score. A significant association was present in both APOE4 carriers (p = .019) and non-carriers (p = .029). Conclusions: Prior studies evaluating the association between VEGF-A levels and cognition have been conflicted. This study is the first to examine whether VEGF-A may be linked to early changes in brain network connectivity which precede cognitive decline. These findings suggest that VEGF-A may be elevated early in the progression of neurocognitive disorders. Whether higher levels of VEGF-A contribute to the pathogenesis of neurocognitive disorders or play a protective role in persevering cognitive function warrants further investigation.

Effect of intervention of music-assisted therapy on physiological parameters of premature babies - A randomized trial

PurposeTo investigate the effect of intervention of music-assisted therapy (MAT) on the physiological parameters of premature babies. MethodsA two-arm parallel-group randomized controlled trial. This study randomly enrolled a total of 41, 28-to-34-week-old premature babies as the subjects to measure their physiological parameters (body temperature, heartrate, respiration, and blood oxygen level). The control group (n = 20) received general routine care, the experimental group (n = 21) received the intervention of MAT (oriental Nanguan music) for three consecutive days, and the data were collected for the following three days after the intervention. ResultsThe results showed that compared with the premature babies receiving general routine care, there were statistically significant differences (p < 0.05) in the heartrate and blood oxygen level in those receiving the MAT (experimental group). However, there was no statistically significant difference in body temperature and respiration. ConclusionThe heartrate, respiration, and blood oxygen level in the premature babies receiving the MAT were gradually stabilized. In addition, this study also verified that oriental Nanguan music, which has a low frequency and a simple melody, could stabilize the physiological parameters and sleep behavior of premature babies. This study could provide an auxiliary care method for the developmental care of premature babies. In the future, it is hoped that MAT can be included into the regular curriculum of nursing education to provide family-centered holistic care, reduce the stress and anxiety of parents of premature babies, and improve the clinical quality of care indicators.

Assessment of brainstem function and haemodynamics by MRI: challenges and clinical prospects.

MRI offers techniques for non-invasively measuring a range of aspects of brain tissue function. Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is widely used to assess neural activity, based on the brain's haemodynamic response, while arterial spin labelling (ASL) MRI is a non-invasive method of quantitatively mapping cerebral perfusion. Both techniques can be applied to measure cerebrovascular reactivity (CVR), an important marker of the health of the cerebrovascular system. BOLD, ASL and CVR have been applied to study a variety of disease processes and are already used in certain clinical circumstances. The brainstem is a critical component of the central nervous system and is implicated in a variety of disease processes. However, its function is difficult to study using MRI because of its small size and susceptibility to physiological noise. In this article, we review the physical and biological underpinnings of BOLD and ASL and their application to measure CVR, discuss the challenges associated with applying them to the brainstem and the opportunities for brainstem MRI in the research and clinical settings. With further optimisation, functional MRI techniques could feasibly be used to assess brainstem haemodynamics and neural activity in the clinical setting.

Clinical Efficacy of Ulinastatin Combined with Azithromycin in the Treatment of Severe Pneumonia in Children and the Effects on Inflammatory Cytokines and Oxidative Stress: A Retrospective Cohort Study.

This retrospective cohort study aimed to evaluate the clinical efficacy of ulinastatin (UTI) and azithromycin (AZM) combination therapy in treating severe pneumonia in children and its impact on inflammatory cytokines and oxidative stress. This retrospective cohort study was conducted from January 1, 2019, to January 1, 2021, involving pediatric patients diagnosed with severe mycoplasma pneumonia (SMPP). The pediatric patients were divided into two groups: those receiving UTI and AZM combination therapy (treatment group) and those receiving azithromycin alone (control group). We compared the two groups regarding clinical data, disease outcomes, inflammatory cytokines, and oxidative stress levels. Baseline characteristics did not significantly differ between the two groups. UTI, in combination with AZM, significantly improved blood oxygen levels, inflammatory infection markers, and relevant clinical symptoms in patients with SMPP on the 3rd day of treatment. Additionally, it significantly reduced the levels of inflammatory cytokines TNF-a, IL-6, IL-1β, and IL-10, as well as oxidative stress markers GSH and SOD. Combining UTI and AZM can rapidly alleviate clinical symptoms and effectively control the progression of patients with SMPP. Therefore, this treatment approach deserves consideration for clinical promotion and utilization.

BOLD frequency-dependent alterations in resting-state functional connectivity by pallidal deep brain stimulation in patients with Parkinson's disease.

Functional MRI (fMRI) has been used to investigate the therapeutic mechanisms underlying deep brain stimulation (DBS) for Parkinson's disease (PD). However, the alterations in stimulation site-seeded functional connectivity induced by DBS at the internal globus pallidus (GPi) remain unclear. Furthermore, whether DBS-modulated functional connectivity is differentially affected within particular frequency bands remains unknown. The present study aimed to reveal the alterations in stimulation site-seeded functional connectivity induced by GPi-DBS and to examine whether there exists a frequency band effect in blood oxygen level-dependent (BOLD) signals related to DBS. Patients with PD receiving GPi-DBS (n = 28) were recruited for resting-state fMRI with DBS on and DBS off under a 1.5-T MR scanner. Age- and sex-matched healthy controls (n = 16) and DBS-naïve PD patients (n = 24) also received fMRI scanning. The alterations in stimulation site-seeded functional connectivity in the stimulation-on state versus stimulation-off state, as well as the relationship between alterations in connectivity and improvement in motor function induced by GPi-DBS, were examined. Furthermore, the modulatory effect of GPi-DBS on the BOLD signals within the 4 frequency subbands (slow-2 to slow-5) was investigated. Finally, the functional connectivity of the motor-related network, consisting of multiple cortical and subcortical regions, was also examined among the groups. In this study, p < 0.05 with Gaussian random field correction indicates statistical significance. Functional connectivity seeding from the stimulation site (i.e., the volume of tissue activated [VTA]) increased in the cortical sensorimotor areas and decreased in the prefrontal regions with GPi-DBS. Alterations in connectivity between the VTA and the cortical motor areas were correlated with motor improvement by pallidal stimulation. The alterations in connectivity were dissociable between the frequency subbands in the occipital and cerebellar areas. The motor network analysis indicated decreased connectivity among most cortical and subcortical regions but increased connectivity between the motor thalamus and the cortical motor area in patients with GPi-DBS compared with those in DBS-naïve patients. The DBS-induced decrease in several cortical-subcortical connectivities within the slow-5 band correlated with motor improvement with GPi-DBS. These findings indicate that the alterations in functional connectivity from the stimulation site to the cortical motor areas, as well as multiple connectivities among the motor-related network, were associated with the efficacy of GPi-DBS for PD. Furthermore, the changing pattern of functional connectivity within the 4 BOLD frequency subbands is partially dissociable.

53 Working Memory Network Load Engagement in Schizophrenia

Objective:Cognitive deficits in patients diagnosed with schizophrenia are a core feature of the disorder. There are currently no treatments for these cognitive deficits. Our aim was to examine and compare patterns of increased versus decreased activity in the central executive network (CEN), salience network (SN), and default mode network (DMN) between healthy controls (HCs) and patients diagnosed with schizophrenia (SZs) as well as to explore the influence of task load on these networks between HCs and SZs.Participants and Methods:Analyses focused on a secondary dataset comprising Blood Oxygen-Level Dependent (BOLD) data collected from 25 HCs and 27 SZs who completed a working memory (WM) task (N-back) with 5 load conditions while undergoing functional magnetic resonance imaging (fMRI). Region of interest (ROI) data were analyzed using linear mixed-effects models.Results:Group activation differences were found in the posterior salience network (pSN), default mode network (DMN), dorsal default mode network (dDMN), and ventral default mode network (vDMN) showing greater activity for SZs. Specifically, pSN, DMN, dDMN, and vDMN all showed increased activity in SZs compared to HCs. The curve of brain activity was consistent between HCs and SZs with the exception of the vDMN, where HCs show greater activation at modest mental workload (quadratic curve) and SZs showed greater brain activation at lower mental workload (linear). In the CEN, there were no group differences, and the response curve was the same for both groups.Conclusions:These group differences demonstrate network difference between HCs and SZs and could show value in treatments targeting cognitive deficits in SZs from a large-scale brain network connectivity perspective. Future studies are needed to confirm these results with larger sample size in order to examine potential subtleties of interactions between these networks.