Fractional amplitude of low-frequency fluctuation and voxel-mirrored homotopic connectivity in patients with persistent postural-perceptual dizziness: resting-state functional magnetic resonance imaging study.

PURPOSE: Persistent postural-perception dizziness (PPPD) is a chronic subjective form of dizziness characterized by the exacerbation of dizziness with active or passive movement, complex visual stimuli, and upright posture. Therefore, we aimed to analyze the resting-state functional magnetic resonance imaging (fMRI) in patients with PPPD using fractional amplitude of low-frequency fluctuation (fALFF) and voxel-mirrored homotopic connectivity (VMHC) and evaluate the correlation between abnormal regions in the brain and clinical features to investigate the pathogenesis of PPPD. METHODS: Thirty patients with PPPD (19 females and 11 males) and 30 healthy controls (HC) (18 females and 12 males) were closely matched for age and sex. The fALFF and VMHC methods were used to investigate differences in fMRI (BOLD sequences) between the PPPD and HC groups and to explore the associations between areas of functional abnormality and clinical characteristics (Dizziness, Anxiety, Depression, and Duration). RESULT: Compared to the HC group, patients with PPPD displayed different functional change patterns, with increased fALFF in the right precuneus and decreased VMHC in the bilateral precuneus. Additionally, patients with PPPD had a positive correlation between precuneus fALFF values and dizziness handicap inventory (DHI) scores, and a negative correlation between VMHC values and the disease duration. CONCLUSIONS: Precuneus dysfunction was observed in patients with PPPD. The fALFF values correlated with the degree of dizziness in PPPD, and changes in VMHC values were associated with the duration of dizziness, suggesting that fMRI changes in the precuneus of patients could be used as a potential imaging marker for PPPD.

Reduced coupling between global signal and cerebrospinal fluid inflow in patients with depressive disorder: A resting state functional MRI study.

BACKGROUND: Depressed patients often suffer from sleep disturbance, which has been recognized to be responsible for glymphatic dysfunction. The purpose of this study was to investigate the coupling strength of global blood­oxygen-level-dependent (gBOLD) signals and cerebrospinal fluid (CSF) inflow dynamics, which is a biomarker for glymphatic function, in depressed patients and to explore its potential relationship with sleep disturbance by using resting-state functional MRI. METHODS: A total of 138 depressed patients (112 females, age: 34.70 ± 13.11 years) and 84 healthy controls (29 females, age: 36.6 ± 11.75 years) participated in this study. The gBOLD-CSF coupling strength was calculated to evaluate glymphatic function. Sleep disturbance was evaluated using the insomnia items (item 4 for insomnia-early, item 5 for insomnia-middle, and item 6 for insomnia-late) of The 17-item Hamilton Depression Rating Scale for depressed patients, which was correlated with the gBOLD-CSF coupling strength. RESULTS: The depressed patients exhibited weaker gBOLD-CSF coupling relative to healthy controls (p = 0.022), possibly due to impairment of the glymphatic system. Moreover, the gBOLD-CSF coupling strength correlated with insomnia-middle (r = 0.097, p = 0.008) in depressed patients. Limitations This study is a cross-sectional study. CONCLUSION: Our findings shed light on the pathophysiology of depression, indicating that cerebral waste clearance system deficits are correlated with poor sleep quality in depressed patients.

Exploring timescale-specific functional brain networks and their associations with aging and cognitive performance in a healthy cohort without dementia.

INTRODUCTION: Functional brain networks (FBNs) coordinate brain functions and are studied in fMRI using blood-oxygen-level-dependent (BOLD) signal correlations. Previous research links FBN changes to aging and cognitive decline, but various physiological factors influnce BOLD signals. Few studies have investigated the intrinsic components of the BOLD signal in different timescales using signal decomposition. This study aimed to explore differences between intrinsic FBNs and traditional BOLD-FBN, examining their associations with age and cognitive performance in a healthy cohort without dementia. MATERIALS AND METHODS: A total of 396 healthy participants without dementia (men = 157; women = 239; age range = 20-85 years) were enrolled in this study. The BOLD signal was decomposed into several intrinsic signals with different timescales using ensemble empirical mode decomposition, and FBNs were constructed based on both the BOLD and intrinsic signals. Subsequently, network features-global efficiency and local efficiency values-were estimated to determine their relationship with age and cognitive performance. RESULTS: The findings revealed that the global efficiency of traditional BOLD-FBN correlated significantly with age, with specific intrinsic FBNs contributing to these correlations. Moreover, local efficiency analysis demonstrated that intrinsic FBNs were more meaningful than traditional BOLD-FBN in identifying brain regions related to age and cognitive performance. CONCLUSIONS: These results underscore the importance of exploring timescales of BOLD signals when constructing FBN and highlight the relevance of specific intrinsic FBNs to aging and cognitive performance. Consequently, this decomposition-based FBN-building approach may offer valuable insights for future fMRI studies.

Multi-Echo Complex Quantitative Susceptibility Mapping and Quantitative Blood Oxygen Level-Dependent Magnitude (mcQSM + qBOLD or mcQQ) for Oxygen Extraction Fraction (OEF) Mapping.

Oxygen extraction fraction (OEF), the fraction of oxygen that tissue extracts from blood, is an essential biomarker used to directly assess tissue viability and function in neurologic disorders. In ischemic stroke, for example, increased OEF can indicate the presence of penumbra-tissue with low perfusion yet intact cellular integrity-making it a primary therapeutic target. However, practical OEF mapping methods are not currently available in clinical settings, owing to the impractical data acquisitions in positron emission tomography (PET) and the limitations of existing MRI techniques. Recently, a novel MRI-based OEF mapping technique, termed QQ, was proposed. It shows high potential for clinical use by utilizing a routine sequence and removing the need for impractical multiple gas inhalations. However, QQ relies on the assumptions of Gaussian noise in susceptibility and multi-echo gradient echo (mGRE) magnitude signals for OEF estimation. This assumption is unreliable in low signal-to-noise ratio (SNR) regions like disease-related lesions, risking inaccurate OEF estimation and potentially impacting clinical decisions. Addressing this, our study presents a novel multi-echo complex QQ (mcQQ) that models realistic Gaussian noise in mGRE complex signals. We implemented mcQQ using a deep learning framework (mcQQ-NET) and compared it with the existing QQ-NET in simulations, ischemic stroke patients, and healthy subjects, using identical training and testing datasets and schemes. In simulations, mcQQ-NET provided more accurate OEF than QQ-NET. In the subacute stroke patients, mcQQ-NET showed a lower average OEF ratio in lesions relative to unaffected contralateral normal tissue than QQ-NET. In the healthy subjects, mcQQ-NET provided uniform OEF maps, similar to QQ-NET, but without unrealistically high OEF outliers in areas of low SNR, such as SNR ≤ 15 (dB). Therefore, mcQQ-NET improves OEF accuracy by more accurately reflecting realistic Gaussian noise in complex mGRE signals. Its enhanced sensitivity to OEF abnormalities, based on more realistic biophysics modeling, suggests that mcQQ-NET has potential for investigating tissue variability in neurologic disorders.

Evaluation of Kidney Injury Using Arterial Spin Labeling and Blood Oxygen Level-Dependent MRI: An Experimental Study in Rats With Carbon Tetrachloride-Induced Liver Cirrhosis.

BACKGROUND: Serum creatinine (Scr) may be not suited to timely and accurately reflect kidney injury related to chronic liver disease. Currently, the ability of arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) sequences to evaluate renal blood flow (RBF) and blood oxygen in chronic liver disease remains to be verified. PURPOSE: To investigate the value of ASL and BOLD imaging in evaluating hemodynamics and oxygenation changes during kidney injury in an animal model of chronic liver disease. STUDY TYPE: Prospective. ANIMAL MODEL: Chronic liver disease model was established by subcutaneous injection of carbon tetrachloride. Forty-three male Sprague-Dawley rats (8 weeks) were divided into a pathological group (0, 2, 4, 6, 8, 12 weeks, each group: N = 6) and a continuous-scanning group (N = 7). FIELD STRENGTH/SEQUENCE: 3-T, ASL, BOLD, and T2W. ASSESSMENT: Regions of interest in the cortex (CO), outer stripe of the outer medulla (OSOM), and inner stripe of the outer medulla (ISOM) are manually delineated. The RBF and T2* values at each time point (0, 2, 4, 6, 8, 12 weeks) are measured and compared. Hematoxylin-eosin score (HE Score, damage area scoring method), alpha-smooth muscle actin (α-SMA), hypoxia-inducible factor-1alpha (HIF-1α), peritubular capillar (PTC) density, Scr, and neutrophil gelatinase-associated lipocalin were harvested. STATISTICAL TESTS: Analysis of variance, Spearman correlation analysis, Kruskal-Wallis tests, and receiver operating characteristic analysis with the area under the curve (AUC). A P-value <0.05 was considered statistically significant. RESULTS: Renal RBF and T2* values of CO, OSOM, and ISOM were significantly different from baseline. Both RBF and T2* were significantly correlated with HE Score, α-SMA, HIF-1α, and PTC density (|r| = 0.406-0.853). RBF demonstrated superior diagnostic capability in identifying severe kidney injury in this model of chronic liver disease (AUC = 0.964). DATA CONCLUSION: Imaging by ASL and BOLD may detect renal hemodynamics and oxygenation changes related to chronic liver disease early. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

The value of functional magnetic resonance imaging in evaluating renal allograft function.

BACKGROUND: To explore the value of arterial spin labeled (ASL) and blood oxygen level dependent (BOLD) imaging in evaluating allogeneic kidney function after renal transplantation. METHODS: One hundred and thirty-five renal transplant patients were included. Demographic and imaging data were collected. Transplanted renal function, pathology, ASL and BOLD parameters were obtained. The patients were divided into normal, mild and severe injury group. The correlation between BOLD/ASL parameters and clinical data were evaluated. The prediction models were based on ASL and BOLD parameters using multivariate logistic analysis. Cox proportional hazards regression model was used to analyze the effects of gender, age, ASL and BOLD on the survival of renal transplant patients. RESULTS: ASL and BOLD parameters were independently associated with renal function injury and renal allograft positive pathology. The AUC of prediction model for renal allograft function based on ASL and BOLD parameters was 0.85, while the AUC based on BOLD parameters was 0.70. Renal transplantation time showed a positive correlation with age, BOLD parameters and SCr，while a negative correlation with ASL parameters and eGFR. ASL parameter was positively correlated with eGFR and negatively correlated with Scr. BOLD parameter was negatively correlated with eGFR, ASL and positively correlated with Scr. Cox proportional hazards regression model showed that the increase of age could reduce the risk of renal function injury and positive pathology. CONCLUSIONS: ASL and BOLD were associated with renal function injury and renal allograft positive pathology. ASL and BOLD had some value in predicting renal allograft function.

The significance and limited influence of cerebrovascular reactivity on age and sex effects in task- and resting-state brain activity.

Functional MRI measures the blood-oxygen-level dependent signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state blood-oxygen-level dependent activity and may confound inter-individual effects, such as those related to aging and biological sex. We examined a large dataset containing breath-holding, checkerboard, and resting-state tasks. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and quantified resting-state activity with amplitude of low-frequency fluctuations and regional homogeneity. We hypothesized that cerebrovascular reactivity would be correlated with blood-oxygen-level dependent measures and that accounting for these correlations would result in better estimates of age and sex effects. We found that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with amplitude of low-frequency fluctuations and regional homogeneity in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in amplitude of low-frequency fluctuations and regional homogeneity. However, correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.

Phytomedicine Fructus Aurantii-derived two absorbed compounds unlock antidepressant and prokinetic multi-functions via modulating 5-HT3/GHSR.

ETHNOPHARMACOLOGICAL RELEVANCE: Fructus Aurantii (FA), a well-known phytomedicine, has been employed to evoke antidepressant and prokinetic multi-functions. Therein, systematically identifying bioactive components and the referred mechanism is essential for FA. AIM OF THE STUDY: This study was planned to answer "2 W" (What and Why), such as which components and pathways contribute to FA's multi-functions. We aimed to identify bioactive compounds as the key for opening the lock of FA's multi-functions, and the molecule mechanisms are their naturally matched lock cylinder. MATERIALS AND METHODS: The phytochemical content of FA extract was determined, and the compounds were identified in rats pretreated with FA using liquid chromatography with mass spectrometry (LC-MS). The contribution strategy was used to assess bioactive compounds' efficacy (doses = their content in FA) in model rats with the mechanism. The changes in functional brain regions were determined via 7.0 T functional magnetic resonance imaging-blood oxygen level-dependent (fMRI-BOLD). RESULT: Eight phytochemicals' content was detected, and merely six components were identified in rats in vivo. Meranzin hydrate + hesperidin (MH), as the primary contributor of FA, exerted antidepressant and prokinetic effects (improvement of indexes for immobility time, gastric emptying, intestinal transit, CRH, ghrelin, ACTH, DA, NA, 5-HT, CORT, and 5-HT3) by regulating 5-HT3/Growth hormone secretagogue receptor (GHSR) pathway. These results were validated by 5-HT2A, 5-HT3, and GHSR receptor antagonists combined with molecule docking. MH restored the excessive BOLD activation of the left accumbens nucleus, left corpus callosum and hypothalamus preoptic region. CONCLUSION: Absorbed MH accounts for FA's anti-depressant and prokinetic efficacy in acutely-stressed rats, primarily via 5-HT3/GHSR shared regulation.

Modulation of temporal and occipital cortex by acupuncture in non-menstrual MWoA patients: a rest BOLD fMRI study.

OBJECTIVE: To investigate the changes in amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) values before and after acupuncture in young women with non-menstrual migraine without aura (MWoA) through rest blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI). METHODS: Patients with non-menstrual MWoA (Group 1, n = 50) and healthy controls (Group 2, n = 50) were recruited. fMRI was performed in Group 1 at 2 time points: before acupuncture (time point 1, TP1); and after the end of all acupuncture sessions (time point 2, TP2), and performed in Group 2 as a one-time scan. Patients in Group 1 were assessed with the Migraine Disability Assessment Questionnaire (MIDAS) and the Short-Form McGill Pain Questionnaire (SF-MPQ) at TP1 and TP2 after fMRI was performed. The ALFF and DC values were compared within Group 1 at two time points and between Group 1 and Group2. The correlation between ALFF and DC values with the statistical differences and the clinical scales scores were analyzed. RESULTS: Brain activities increased in the left fusiform gyrus and right angular gyrus, left middle occipital gyrus, and bilateral prefrontal cortex and decreased in left inferior parietal lobule in Group 1, which had different ALFF values compared with Group 2 at TP1. The bilateral fusiform gyrus, bilateral inferior temporal gyrus and right middle temporal gyrus increased and right angular gyrus, right superior marginal gyrus, right inferior parietal lobule, right middle occipital gyrus, right superior frontal gyrus, right middle frontal gyrus, right anterior central gyrus, and right supplementary motor area decreased in activity in Group 1 had different DC values compared with Group 2 at TP1. ALFF and DC values of right inferior temporal gyrus, right fusiform gyrus and right middle temporal gyrus were decreased in Group1 at TP1 compared with TP2. ALFF values in the left middle occipital area were positively correlated with the pain degree at TP1 in Group1 (correlation coefficient r, r = 0.827, r = 0.343; P < 0.01, P = 0.015). The DC values of the right inferior temporal area were positively correlated with the pain degree at TP1 in Group 1 (r = 0.371; P = 0.008). CONCLUSION: Spontaneous brain activity and network changes in young women with non-menstrual MwoA were altered by acupuncture. The right temporal area may be an important target for acupuncture modulated brain function in young women with non-menstrual MwoA.

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.

Functional-structural decoupling in visual network is associated with cognitive decline in patients with type 2 diabetes mellitus: evidence from a multimodal MRI analysis.

Type 2 diabetes mellitus (T2DM) and cognitive dysfunction are highly prevalent disorders worldwide. Although visual network (VN) alteration and functional-structural coupling are potential warning factors for mild cognitive impairment (MCI) in T2DM patients, the relationship between the three in T2DM without MCI is unclear. Thirty T2DM patients without MCI and twenty-nine healthy controls (HC) were prospectively enrolled. Visual components (VC) were estimated by independent component analysis (ICA). Degree centrality (DC), amplitude of low frequency fluctuation (ALFF) and fractional anisotropy (FA) were established to reflect functional and structural characteristics in these VCs respectively. Functional-structural coupling coefficients were further evaluated using combined FA and DC or ALFF. Partial correlations were performed among neuroimaging indicators and neuropsychological scores and clinical variables. Three VCs were selected using group ICA. Deteriorated DC, ALFF and DC-FA coefficients in the VC1 were observed in the T2DM group compared with the HC group, while FA and ALFF-FA coefficients in these three VCs showed no significant differences. In the T2DM group, DC in the VC1 positively correlated with 2 dimensions in the California Verbal Learning Test, including Trial 4 and Total trial 1-5. The impaired DC-FA coefficients in the VC1 markedly affected the Total perseverative responses % of the Wisconsin Card Sorting Test. These findings indicate that DC and DC-FA coefficients in VN may be potential imaging biomarkers revealing early cognitive deficits in T2DM.

Remote photoplethysmography-based human vital sign prediction using cyclical algorithm.

This article aims to predict vital signs like heart rate (HR), respiration rate, and arterial oxygen saturation using ambient light video, eliminating chronic distortions through improved frame quality with BER estimation. The study employs the cascade residual CNN-FPNR technique for preprocessing and SNR enhancement using energy variance maximization. The image cascade network (ICNet) facilitates segmentation, achieving strong segmentation in low-light ambient videos. Remote photoplethysmography (iPPG) enables noncontact vital sign monitoring, predicting HR and respiratory rate (RR). An innovative noninvasive temperature and cyclical algorithm, incorporating principal component analysis and fast Fourier transform, evaluate patient HR and RR. To address challenges related to involuntary movements, a dynamic time-warping-based optimization method is used for precise region selection. The study introduces an intensity variance-based threshold analysis for arterial oxygen saturation level determination. Ultimately, the support vector machine (SVM) classification technique evaluates the ground truth, showcasing the system's promising potential for remote and accurate vital sign assessment.

Changes in the BOLD signal of S1 and BA3 per finger/phalanx as a response to high-frequency vibratory stimulation.

PURPOSE AND METHOD: The purpose of this study was to determine the changes in the Blood Oxygen Level Dependent signal of Primary somatosensory area (S1) and Brodmann area 3 (BA3) per finger and phalanx in comparison to the activation voxel when 250 Hz vibratory stimulation with high sensitivity for the Pacinian corpuscle was given to the four fingers and three phalanges. RESULTS: The result of analyzing the activation voxel showed a significant difference for S1 per finger and phalanx, but for BA3, no significant difference was observed despite a similar trend to S1. In contrast, the activation intensity (BOLD) displayed a significant difference for S1 per finger and phalanx and for BA3, where the activation voxel had no significant variation. In addition, while the result of S1 did not indicate whether the index or the little fingers had the highest sensitivity based on the BOLD signal per finger, the result of BA3 marked the strongest BOLD signal for the little finger as a response to 250 Hz vibratory stimulation. The activation intensity per phalanx was the highest for the intermediate phalanx for S1 and BA3, which was in line with a previous study comparing the activation voxel. CONCLUSIONS: The method based on the intensity of the nerve activation is presumed to have high sensitivity as the signal intensity is monitored within a specific, defined area. Thus, for the extraction of brain activation patterns of micro-domains, such as BA3, monitoring the BOLD signal that reflects the nerve activation intensity more sensitively is likely to be advantageous.

Multifaceted neural and vascular pathologies after pediatric mild traumatic brain injury.

Dynamic changes in neurodevelopment and cognitive functioning occur during adolescence, including a switch from reactive to more proactive forms of cognitive control, including response inhibition. Pediatric mild traumatic brain injury (pmTBI) affects these cognitions immediately post-injury, but the role of vascular versus neural injury in cognitive dysfunction remains debated. This study consecutively recruited 214 sub-acute pmTBI (8-18 years) and age/sex-matched healthy controls (HC; N = 186), with high retention rates (>80%) at four months post-injury. Multimodal imaging (functional MRI during response inhibition, cerebral blood flow and cerebrovascular reactivity) assessed for pathologies within the neurovascular unit. Patients exhibited increased errors of commission and hypoactivation of motor circuitry during processing of probes. Evidence of increased/delayed cerebrovascular reactivity within motor circuitry during hypercapnia was present along with normal perfusion. Neither age-at-injury nor post-concussive symptom load were strongly associated with imaging abnormalities. Collectively, mild cognitive impairments and clinical symptoms may continue up to four months post-injury. Prolonged dysfunction within the neurovascular unit was observed during proactive response inhibition, with preliminary evidence that neural and pure vascular trauma are statistically independent. These findings suggest pmTBI is characterized by multifaceted pathologies during the sub-acute injury stage that persist several months post-injury.

Blood Oxygen Level-Dependent MR Imaging of Lower Extremities in Peripheral Artery Disease and Its Correlation With Walking Performance.

BACKGROUND: A noninvasive and reliable approach to quantitatively measure muscle perfusion of lower extremity is needed to aid the diagnosis and treatment of peripheral artery disease (PAD). PURPOSE: To verify the reproductivity of using blood oxygen level-dependent (BOLD) imaging to evaluate perfusion in lower extremities, and explore its correlation with walking performance in patients with PAD. STUDY TYPE: Prospective observational study. SUBJECTS: Seventeen patients with lower extremity PAD (mean age: 67 ± 6 years, 15 males) and eight older adults (controls). FIELD STRENGTH/SEQUENCE: Dynamic multi-echo gradient echo T2* weighted imaging at 3T. ASSESSMENT: Perfusion was analyzed in regions of interest according to muscle groups. Perfusion parameters were measured, such as minimum ischemia value (MIV), time to peak (TTP), and gradient during reactive hyperemia (Grad) by two independent users. Walking performance experiments including short physical performance battery (SPPB) and 6-minute walk were tested in patients. STATISTICAL TESTS: BOLD parameters were compared using Mann-Whitney U test and Kruskal-Wallis test. Relations between parameters and walking performance were assessed by Mann-Whitney U test and Spearman's correlation coefficient. RESULTS: Good to perfect agreement was demonstrated for all perfusion parameters of interuser reproducibility, and the interscan reproducibility of MIV, TTP, and Grad was good. The TTP of the patients was longer than that of the controls (87.85 ± 38.85 s vs. 36.54 ± 7.27 s), while the Grad of patients was smaller (0.16 ± 0.12 msec/s vs. 0.24 ± 0.11 msec/s). Among PAD patients, the MIV was significantly lower in the low SPPB subgroup (score 6-8) than in the high SPPB group (score 9-12), and the TTP was negatively correlated with 6-minute walk distance (ρ = -0.549). DATA CONCLUSION: BOLD imaging method had overall good reproducibility for the perfusion assessment of calf muscles. The perfusion parameters were different between PAD patients and controls, and were correlated with lower extremity function. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Predicting dissolved oxygen level using Young's double-slit experiment optimizer-based weighting model.

Accurate prediction of the dissolved oxygen level (DOL) is important for enhancing environmental conditions and facilitating water resource management. However, the irregularity and volatility inherent in DOL pose significant challenges to achieving precise forecasts. A single model usually suffers from low prediction accuracy, narrow application range, and difficult data acquisition. This study proposes a new weighted model that avoids these problems, which could increase the prediction accuracy of the DOL. The weighting constructs of the proposed model (PWM) included eight neural networks and one statistical method and utilized Young's double-slit experimental optimizer as an intelligent weighting tool. To evaluate the effectiveness of PWM, simulations were conducted using real-world data acquired from the Tualatin River Basin in Oregon, United States. Empirical findings unequivocally demonstrated that PWM outperforms both the statistical model and the individual machine learning models, and has the lowest mean absolute percentage error among all the weighted models. Based on two real datasets, the PWM can averagely obtain the mean absolute percentage errors of 1.0216%, 1.4630%, and 1.7087% for one-, two-, and three-step predictions, respectively. This study shows that the PWM can effectively integrate the distinctive merits of deep learning methods, neural networks, and statistical models, thereby increasing forecasting accuracy and providing indispensable technical support for the sustainable development of regional water environments.

Hybrid deep learning model based smart IOT based monitoring system for Covid-19.

Recently, COVID-19 becomes a hot topic and explicitly made people follow social distancing and quarantine practices all over the world. Meanwhile, it is arduous to visit medical professionals intermittently by the patients for fear of spreading the disease. This IoT-based healthcare monitoring system is utilized by many professionals, can be accessed remotely, and provides treatment accordingly. In context with this, we designed an IoT-based healthcare monitoring system that sophisticatedly measures and monitors the parameters of patients such as oxygen level, blood pressure, temperature, and heart rate. This system can be widely used in rural areas that are linked to the nearest city hospitals to monitor the patients. The collected data from the monitoring system are stored in the cloud-based data storage and for the classification our approach proposes an innovative Recurrent Convolutional Neural Network (RCNN) based Puzzle optimization algorithm (PO). Based on the outcome further treatments are made with the assistance of physicians. Experimental analyses are made and analyzed the performance with state-of-art works. The availability of more data storage capacity in the cloud can make physicians access the previous data effortlessly.

COVID-19 during pregnancy could potentially affect placental function.

OBJECTIVE: COVID-19 is an ongoing pandemic and has been extensively studied. However, the effects of COVID-19 during pregnancy, particularly on placental function, have not been verified. In this study, we used blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) to evaluate whether COVID-19 incidence during pregnancy has any lasting effects with respect to placental oxygenation. METHODS: This is a case-control study, in which eight cases of singleton pregnancies before 30 weeks gestation with COVID-19 mothers were included. Placental oxygenation was evaluated using BOLD-MRI after 32 weeks of gestation. BOLD-MRI was consecutively performed under normoxia (21% O2), hyperoxia (100% O2), and normoxia for 4 min each. Individual placental time-activity curves were evaluated to calculate the peak score (peakΔR2*) and the time from the start of maternal oxygen administration to the time of peakΔR2* (time to peakΔR2*). Eighteen COVID-19-free normal pregnancies from a previous study were used as the control group. RESULTS: No significant differences were found between the two groups regarding maternal background, number of days of delivery, birth weight, and placental weight. The parameter peakΔR2* was significantly decreased in the COVID-19 group (8 ± 3 vs. 5 ± 1, p < .001); however, there was no significant difference in time to peakΔR2* (458 ± 74 s vs. 471 ± 33 s, p = .644). CONCLUSIONS: In this study, BOLD-MRI was used to evaluate placental oxygenation during pregnancy in COVID-19-affected patients. COVID-19 during pregnancy decreased placental oxygenation even post-illness, but had no effect on fetal growth; further investigation of the possible effects of COVID-19 on the fetus and mother is warranted.

Associations between neurovascular coupling and cerebral small vessel disease: A systematic review and meta-analysis.

PURPOSE: The pathogenesis of cerebral small vessel disease (cSVD) remains elusive despite evidence of an association between white matter hyperintensities (WMH) and endothelial cerebrovascular dysfunction. Neurovascular coupling (NVC) may be a practical alternative measure of endothelial function. We performed a systematic review of reported associations between NVC and cSVD. METHODS: EMBASE and PubMed were searched for studies reporting an association between any STRIVE-defined marker of cSVD and a measure of NVC during functional magnetic resonance imaging, transcranial Doppler, positron emission tomography, near-infrared spectroscopy or single-photon emission computed tomography, from inception to November 3rd, 2022. Where quantitative data was available from studies using consistent tests and analyses, results were combined by inverse-variance weighted random effects meta-analysis. FINDINGS: Of 29 studies (19 case-controls; 10 cohorts), 26 reported decreased NVC with increasing severity of cSVD, of which 18 were individually significant. In 28 studies reporting associations with increasing WMH, 25 reported reduced NVC. Other markers of cSVD were associated with reduced NVC in: eight of nine studies with cerebral microbleeds (six showing a significant effect); three of five studies with lacunar stroke; no studies reported an association with enlarged perivascular spaces. Specific SVD diseases were particularly associated with reduced NVC, including six out of seven studies in cerebral amyloid angiopathy and all four studies in CADASIL. In limited meta-analyses, %BOLD occipital change to a visual stimulus was consistently reduced with more severe WMH (seven studies, SMD -1.51, p < 0.01) and increasing microbleeds (seven studies, SMD -1.31, p < 0.01). DISCUSSION AND CONCLUSION: In multiple, small studies, neurovascular coupling was reduced in patients with increasing severity of all markers of cSVD in sporadic disease, CAA and CADASIL. Cerebrovascular endothelial dysfunction, manifest as impaired NVC, may be a common marker of physiological dysfunction due to small vessel injury that can be easily measured in large studies and clinical practice.

The Significance and Limited Influence of Cerebrovascular Reactivity on Age and Sex Effects in Task- and Resting-State Brain Activity.

Functional MRI (fMRI) measures the blood-oxygen-level dependent (BOLD) signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state BOLD activity and may confound inter-individual effects observed in BOLD-based measures, such as those related to aging and biological sex. To investigate this, we examined a large open-access fMRI dataset containing a breath-holding task, checkerboard task, and resting-state scans. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and from the resting-state data, we quantified the resting-state amplitude of low-frequency fluctuations (ALFF), and resting-state regional homogeneity (ReHo). We hypothesized that cerebrovascular reactivity would be correlated with BOLD measures and that accounting for these correlations would result in better estimates of age and sex effects. Our analysis showed that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with ALFF and ReHo in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in ALFF and ReHo scores. Finally, we demonstrated that correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.