Detection and prediction of freezing of gait with wearable sensors in Parkinson's disease.

Freezing of gait (FoG) is one of the most distressing symptoms of Parkinson's Disease (PD), commonly occurring in patients at middle and late stages of the disease. Automatic and accurate FoG detection and prediction have emerged as a promising tool for long-term monitoring of PD and implementation of gait assistance systems. This paper reviews the recent development of FoG detection and prediction using wearable sensors, with attention on identifying knowledge gaps that need to be filled in future research. This review searched the PubMed and Web of Science databases to collect studies that detect or predict FoG with wearable sensors. After screening, 89 of 270 articles were included. The data description, extracted features, detection/prediction methods, and classification performance were extracted from the articles. As the number of papers of this area is increasing, the performance has been steadily improved. However, small datasets and inconsistent evaluation processes still hinder the application of FoG detection and prediction with wearable sensors in clinical practice.

EEG Signal Processing Techniques and Applications.

Electroencephalography (EEG) is a widely recognised non-invasive method for capturing brain electrophysiological activity [...].

Brain functional and effective connectivity based on electroencephalography recordings: A review.

Functional connectivity and effective connectivity of the human brain, representing statistical dependence and directed information flow between cortical regions, significantly contribute to the study of the intrinsic brain network and its functional mechanism. Many recent studies on electroencephalography (EEG) have been focusing on modeling and estimating brain connectivity due to increasing evidence that it can help better understand various brain neurological conditions. However, there is a lack of a comprehensive updated review on studies of EEG-based brain connectivity, particularly on visualization options and associated machine learning applications, aiming to translate those techniques into useful clinical tools. This article reviews EEG-based functional and effective connectivity studies undertaken over the last few years, in terms of estimation, visualization, and applications associated with machine learning classifiers. Methods are explored and discussed from various dimensions, such as either linear or nonlinear, parametric or nonparametric, time-based, and frequency-based or time-frequency-based. Then it is followed by a novel review of brain connectivity visualization methods, grouped by Heat Map, data statistics, and Head Map, aiming to explore the variation of connectivity across different brain regions. Finally, the current challenges of related research and a roadmap for future related research are presented.

A Multi-Modal Analysis of the Freezing of Gait Phenomenon in Parkinson's Disease.

BACKGROUND: Freezing of Gait (FOG) is one of the most disabling motor complications of Parkinson's disease, and consists of an episodic inability to move forward, despite the intention to walk. FOG increases the risk of falls and reduces the quality of life of patients and their caregivers. The phenomenon is difficult to appreciate during outpatients visits; hence, its automatic recognition is of great clinical importance. Many types of sensors and different locations on the body have been proposed. However, the advantages of a multi-sensor configuration with respect to a single-sensor one are not clear, whereas this latter would be advisable for use in a non-supervised environment. METHODS: In this study, we used a multi-modal dataset and machine learning algorithms to perform different classifications between FOG and non-FOG periods. Moreover, we explored the relevance of features in the time and frequency domains extracted from inertial sensors, electroencephalogram and skin conductance. We developed both a subject-independent and a subject-dependent algorithm, considering different sensor subsets. RESULTS: The subject-independent and subject-dependent algorithms yielded accuracies of 85% and 88% in the leave-one-subject-out and leave-one-task-out test, respectively. Results suggest that the inertial sensors positioned on the lower limb are generally the most significant in recognizing FOG. Moreover, the performance impairment experienced when using a single tibial accelerometer instead of the optimal multi-modal configuration is limited to 2-3%. CONCLUSIONS: The achieved results disclose the possibility of getting a good FOG recognition using a minimally invasive set-up made of a single inertial sensor. This is very significant in the perspective of implementing a long-term monitoring of patients in their homes, during activities of daily living.

An iPPG-Based Device for Pervasive Monitoring of Multi-Dimensional Cardiovascular Hemodynamics.

Hemodynamic activities, as an essential measure of physiological and psychological characteristics, can be used for cardiovascular and cerebrovascular disease detection. Photoplethysmography imaging (iPPG) can be applied for such purposes with non-contact advances, however, most cardiovascular hemodynamics of iPPG systems are developed for laboratory research, which limits the application in pervasive healthcare. In this study, a video-based facial iPPG detecting equipment was devised to provide multi-dimensional spatiotemporal hemodynamic pulsations for applications with high portability and self-monitoring requirements. A series of algorithms have also been developed for physiological indices such as heart rate and breath rate extraction, facial region analysis, and visualization of hemodynamic pulsation distribution. Results showed that the new device can provide a reliable measurement of a rich range of cardiovascular hemodynamics. Combined with the advanced computing techniques, the new non-contact iPPG system provides a promising solution for user-friendly pervasive healthcare.

Analysis of differential metabolites in lung cancer patients based on metabolomics and bioinformatics.

Aim: Based on metabonomics, the metabolic markers of lung cancer patients were analyzed, combined with bioinformatics to explore the underlying disease mechanism. Materials & methods: Based on case-control design, using UPLC-Q-TOF/MS, urine metabolites were detected in discovery and validation set. Multivariate statistical analysis were performed to identify potential markers for lung cancer. A network analysis was constructed to integrate lung cancer disease targets with the above metabolic markers, and its possible mechanism and biological significance were explained. Results: A total of 35 potential markers were identified, 11 of which overlapped. Five key markers have a good linear correlation with serum biochemical indicators. Conclusion: The occurrence and development of lung cancer are closely related to disturbance of D-Glutamine and D-glutamate metabolism, amino acid imbalance. This test was registered on China clinical trial registration center (www.chictr.org.cn/index.aspx), registration number was ChiCTR1900025543.

A New Proxy Measurement Algorithm with Application to the Estimation of Vertical Ground Reaction Forces Using Wearable Sensors.

Measurement of the ground reaction forces (GRF) during walking is typically limited to laboratory settings, and only short observations using wearable pressure insoles have been reported so far. In this study, a new proxy measurement method is proposed to estimate the vertical component of the GRF (vGRF) from wearable accelerometer signals. The accelerations are used as the proxy variable. An orthogonal forward regression algorithm (OFR) is employed to identify the dynamic relationships between the proxy variables and the measured vGRF using pressure-sensing insoles. The obtained model, which represents the connection between the proxy variable and the vGRF, is then used to predict the latter. The results have been validated using pressure insoles data collected from nine healthy individuals under two outdoor walking tasks in non-laboratory settings. The results show that the vGRFs can be reconstructed with high accuracy (with an average prediction error of less than 5.0%) using only one wearable sensor mounted at the waist (L5, fifth lumbar vertebra). Proxy measures with different sensor positions are also discussed. Results show that the waist acceleration-based proxy measurement is more stable with less inter-task and inter-subject variability than the proxy measures based on forehead level accelerations. The proposed proxy measure provides a promising low-cost method for monitoring ground reaction forces in real-life settings and introduces a novel generic approach for replacing the direct determination of difficult to measure variables in many applications.

A Multi-Graph Cross-Attention-Based Region-Aware Feature Fusion Network Using Multi-Template for Brain Disorder Diagnosis.

Functional connectivity (FC) networks based on resting-state functional magnetic imaging (rs-fMRI) are reliable and sensitive for brain disorder diagnosis. However, most existing methods are limited by using a single template, which may be insufficient to reveal complex brain connectivities. Furthermore, these methods usually neglect the complementary information between static and dynamic brain networks, and the functional divergence among different brain regions, leading to suboptimal diagnosis performance. To address these limitations, we propose a novel multi-graph cross-attention based region-aware feature fusion network (MGCA-RAFFNet) by using multi-template for brain disorder diagnosis. Specifically, we first employ multi-template to parcellate the brain space into different regions of interest (ROIs). Then, a multi-graph cross-attention network (MGCAN), including static and dynamic graph convolutions, is developed to explore the deep features contained in multi-template data, which can effectively analyze complex interaction patterns of brain networks for each template, and further adopt a dual-view cross-attention (DVCA) to acquire complementary information. Finally, to efficiently fuse multiple static-dynamic features, we design a region-aware feature fusion network (RAFFNet), which is beneficial to improve the feature discrimination by considering the underlying relations among static-dynamic features in different brain regions. Our proposed method is evaluated on both public ADNI-2 and ABIDE-I datasets for diagnosing mild cognitive impairment (MCI) and autism spectrum disorder (ASD). Extensive experiments demonstrate that the proposed method outperforms the state-of-the-art methods. Our source code is available at https://github.com/mylbuaa/MGCA-RAFFNet.

Synchronous liver metastasis at initial diagnosis of adrenal pheochromocytoma by CT: A case report.

Pheochromocytoma is a tumor of the sympathetic nervous system, characterized by atypical symptoms and signs. Pheochromocytoma metastases can be found in various tissues and organs. However, synchronous metastasis at the initial diagnosis of pheochromocytoma is rare. The present study described a case with synchronous liver metastasis at the initial diagnosis of adrenal pheochromocytoma based on imaging findings. A 41-year-old woman presented with liver pain and fatigue for 1 month. Physical examination showed increased blood pressure and heart rate with sinus tachycardia. Laboratory examination revealed normal levels of liver tumor markers and increased levels of serum or urine epinephrine and norepinephrine. CT examination revealed a large cystic solid mass in the right lobe of the liver and right adrenal gland, and the solid part of the mass was enhanced after enhancement. The pathological diagnosis was pheochromocytoma of the right adrenal gland with liver metastasis. The patient underwent right hepatectomy and right adrenal tumor resection. During the postoperative follow-up, the patient's blood pressure and catecholamine levels were within the normal range. Three years after surgery, the CT examination revealed multiple liver metastases. Chemotherapy was administered to the patient. A year later, re-examination revealed an increase and enlargement of the metastases, and the mass of the right adrenal gland remained similar to the previous one. After 6 months of follow-up, the patient succumbed to recurrence and metastasis. Preoperative diagnosis of metastatic pheochromocytoma is challenging. This case mainly emphasizes that imaging findings can help the clinical diagnosis of metastatic pheochromocytoma.

SG-Transunet: A segmentation-guided Transformer U-Net model for KRAS gene mutation status identification in colorectal cancer.

Accurately identifying the Kirsten rat sarcoma virus (KRAS) gene mutation status in colorectal cancer (CRC) patients can assist doctors in deciding whether to use specific targeted drugs for treatment. Although deep learning methods are popular, they are often affected by redundant features from non-lesion areas. Moreover, existing methods commonly extract spatial features from imaging data, which neglect important frequency domain features and may degrade the performance of KRAS gene mutation status identification. To address this deficiency, we propose a segmentation-guided Transformer U-Net (SG-Transunet) model for KRAS gene mutation status identification in CRC. Integrating the strength of convolutional neural networks (CNNs) and Transformers, SG-Transunet offers a unique approach for both lesion segmentation and KRAS mutation status identification. Specifically, for precise lesion localization, we employ an encoder-decoder to obtain segmentation results and guide the KRAS gene mutation status identification task. Subsequently, a frequency domain supplement block is designed to capture frequency domain features, integrating it with high-level spatial features extracted in the encoding path to derive advanced spatial-frequency domain features. Furthermore, we introduce a pre-trained Xception block to mitigate the risk of overfitting associated with small-scale datasets. Following this, an aggregate attention module is devised to consolidate spatial-frequency domain features with global information extracted by the Transformer at shallow and deep levels, thereby enhancing feature discriminability. Finally, we propose a mutual-constrained loss function that simultaneously constrains the segmentation mask acquisition and gene status identification process. Experimental results demonstrate the superior performance of SG-Transunet over state-of-the-art methods in discriminating KRAS gene mutation status.

Effect of tissue fixatives on the corrosion of biomedical magnesium alloys.

In this work, the corrosion behavior of pure Mg, Mg3Ag, Mg6Ag, and MgZnYNd alloys in different fixatives (ethyl alcohol (EA), 85 % ethyl alcohol (85 % EA), 10 % neutral buffered formalin (10 % NBF), 4 % glutaric dialdehyde (4 % GD), and 4 % paraformaldehyde (4 % PFA)) was investigated to provide a valuable reference for the selection of fixatives during the histological evaluation of Mg implants. Through the hydrogen evolution test, pH test, and corrosion morphology and product characterization, it was found that corrosion proceeded slowest in the EA and 85 % EA groups, slightly faster in 4 % GD, faster in 10 % NBF, and fastest in 4 % PFA. After corrosion, the EA group surface remained unchanged, while the 85%EA group surface developed minor cracks and warping. The 4%GD fixative formed a dense needle-like protective layer on the Mg substrate. The 10%NBF group initially grew a uniform layer, but later developed irregular pits due to accelerated corrosion. In contrast, the 4%PFA solution caused more severe corrosion attributed to chloride ions. The main corrosion products in the EA and 85%EA groups were MgO and Mg(OH)2, while the other fixatives containing diverse ions also yielded phosphates like Mg3(PO4)2 and MgHPO4. In 4 % PFA, AgCl formed on the surface of Mg6Ag alloy after corrosion. Therefore, to minimize Mg alloy corrosion without compromising staining quality, EA or 85 % EA is recommended, while 4 % PFA is not recommended due to its significant impact.

Identifying differentially expressed genes in goat mammary epithelial cells induced by overexpression of SOCS3 gene using RNA sequencing.

The suppressor of cytokine signaling 3 (SOCS3) is a key signaling molecule that regulates milk synthesis in dairy livestock. However, the molecular mechanism by which SOCS3 regulates lipid synthesis in goat milk remains unclear. This study aimed to screen for key downstream genes associated with lipid synthesis regulated by SOCS3 in goat mammary epithelial cells (GMECs) using RNA sequencing (RNA-seq). Goat SOCS3 overexpression vector (PC-SOCS3) and negative control (PCDNA3.1) were transfected into GMECs. Total RNA from cells after SOCS3 overexpression was used for RNA-seq, followed by differentially expressed gene (DEG) analysis, functional enrichment analysis, and network prediction. SOCS3 overexpression significantly inhibited the synthesis of triacylglycerol, total cholesterol, non-esterified fatty acids, and accumulated lipid droplets. In total, 430 DEGs were identified, including 226 downregulated and 204 upregulated genes, following SOCS3 overexpression. Functional annotation revealed that the DEGs were mainly associated with lipid metabolism, cell proliferation, and apoptosis. We found that the lipid synthesis-related genes, STAT2 and FOXO6, were downregulated. In addition, the proliferation-related genes BCL2, MMP11, and MMP13 were upregulated, and the apoptosis-related gene CD40 was downregulated. In conclusion, six DEGs were identified as key regulators of milk lipid synthesis following SOCS3 overexpression in GMECs. Our results provide new candidate genes and insights into the molecular mechanisms involved in milk lipid synthesis regulated by SOCS3 in goats.

Notch1 signaling is irresponsible to the anti-leukemic effect of HDACis in B-ALL Nalm-6 cells.

B cell acute lymphoblastic leukemia (B-ALL) is an aggressive hematologic malignancy with limited treatment strategies. Histone deacetylases inhibitors (HDACis) are promising novel tools for cancer therapy, whose anti-tumor effects and the underlying mechanisms on B-ALL remain to be elucidated. Recently, Notch1 signaling activation has been reported to be involved in the anti-tumor effects of HDACis. This study was conducted to determine: the influence of two HDACis, valproic acid (VPA) and suberic bishydroxamic acid (SBHA), on Notch1 signaling as well as the role of Notch1 signaling in the anti-tumor effects of HDACis in B-ALL cells. To address this issue, we treated Nalm-6 B-ALL cell line with VPA and SBHA (HDACis), then, cell proliferation, cell cycle, apoptosis, and expression of Notch1 related genes were analyzed. We found that VPA and SBHA dramatically inhibited cell growth, induced a G1/S cell cycle block in accompany with an elevated level of P21(WAF1) protein in Nalm-6 cells. The levels of cleaved caspase-9, caspase-3, and PARP were elevated, indicating the activation of apoptosis. However, no change in the expression of Notch1 and its downstream genes were found by quantitative real-time PCR and Western blot. Our result suggested that Notch1 signaling is irresponsible for the anti-leukemic effect of HDACis in B-ALL cells. New hypotheses and future studies are needed to explore the underlying mechanisms of the anti-cancer effect in B-ALL.

Changes in cerebral autoregulation, stroke-related blood biomarkers, and autonomic regulation after patent foramen ovale closure in severe migraine patients.

AIMS: This study aimed to investigate changes in dynamic cerebral autoregulation (dCA), 20 stroke-related blood biomarkers, and autonomic regulation after patent foramen ovale (PFO) closure in severe migraine patients. METHODS: Patent foramen ovale severe migraine patients, matched non-PFO severe migraine patients, and healthy controls were included. dCA and autonomic regulation were evaluated in each participant at baseline, and within 48-h and 30 days after closure in PFO migraineurs. A panel of stroke-related blood biomarkers was detected pre-surgically in arterial-and venous blood, and post-surgically in the arterial blood in PFO migraineurs. RESULTS: Forty-five PFO severe migraine patients, 50 non-PFO severe migraine patients, and 50 controls were enrolled. The baseline dCA function of PFO migraineurs was significantly lower than that of non-PFO migraineurs and controls but was rapidly improved with PFO closure, remaining stable at 1-month follow-up. Arterial blood platelet-derived growth factor-BB (PDGF-BB) levels were higher in PFO migraineurs than in controls, which was immediately and significantly reduced after closure. No differences in autonomic regulation were observed among the three groups. CONCLUSION: Patent foramen ovale closure can improve dCA and alter elevated arterial PDGF-BB levels in migraine patients with PFO, both of which may be related to the preventive effect of PFO closure on stroke occurrence/recurrence.

Neurosurgical robots in China: State of the art and future prospect.

Neurosurgical robots have developed for decades and can effectively assist surgeons to carry out a variety of surgical operations, such as biopsy, stereo-electroencephalography (SEEG), deep brain stimulation (DBS), and so forth. In recent years, neurosurgical robots in China have developed rapidly. This article will focus on several key skills in neurosurgical robots, such as medical imaging systems, automatic manipulator, lesion localization techniques, multimodal image fusion technology, registration method, and vascular imaging technology; introduce the clinical application of neurosurgical robots in China, and look forward to the potential improvement points in the future based on our experience and research in the field.

A Comparison Between W Score and RYAN Score in Diagnosing Laryngopharyngeal Reflux Disease.

OBJECTIVE: To assess the diagnostic value of the W score in differentiating laryngopharyngeal reflux disease (LPRD) patients from the normal population by pharyngeal pH (Dx-pH) monitoring, compared with the RYAN score. METHODS: One hundred and eight patients with suspected LPRD and complete follow-up results after more than 8 weeks of anti-reflux therapy were enrolled from the Department of Otolaryngology-Head and Neck Surgery, Gastroenterology and Respiratory Medicine of seven hospitals. Their Dx-pH monitoring data before treatment were reanalyzed to obtain the W score in addition to the RYAN score and then the diagnostic sensitivity and specificity were compared and evaluated with reference to the result of anti-reflux therapy. RESULTS: In eighty-seven (80.6%) cases, anti-reflux therapy was effective, and in 21 patients (19.4%), therapy was ineffective. Twenty-seven patients (25.0%) had a positive RYAN score. The W score was positive in 79 (73.1%) patients. There were 52 patients who had a negative RYAN score, but a positive W score. The diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of the RYAN score were 28.7%, 90.5%, 92.6%, and 23.5%, respectively (kappa = 0.092, P = 0.068), whereas those of the W score for LPRD was 83.9%, 71.4%, 92.4%, and 51.7%, respectively (kappa = 0.484, P < 0.001). CONCLUSIONS: W score is much more sensitive for the diagnosis of LPRD. Prospective studies with larger patient populations are necessary to validate and improve diagnostic efficacy. TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR1800014931.

Puncture of foramen ovale cranium in computed tomography three-dimensional reconstruction.

The study aimed to provide the anatomic data for puncture of foramen ovale cranium in oral cavity. We scan 100 volunteers' skull on computed tomography who have no lesion of skull base, of which the images were for three-dimensional reconstruction. The following observations and measurements were carried out: the shape, size of foramen ovale cranium, and the angle and length of puncture line. The results we got are the following: foramen ovale cranium appears as oval, kidney shape, round, pear shape, and strip shape. Foramen ovale diameter is 8.20 ± 1.54 mm, and width is 4.08 ± 0.73 mm for men and 4.23 ± 0.79 mm for female. The distance from the center of foramen ovale to the maxillary second molar is 51.65 mm for male and 48.77 mm for female. The puncture line is from the center of foramen ovale to the maxillary second molar. The angle of the puncture line with the vertical plane, which is through the midpoint of supraorbital margin and the infraorbital margin, is 40.27 degrees for men and 37.31 degrees for women. The angle of the puncture line with the horizontal plane is 49.37 degrees for men and 52.26 degrees for women. The angle of the puncture line with the sagittal plane is 3.78 degrees. All data between the left and right sides have no statistically significant difference (P > 0.05), but the diameter, the length of the puncture, and the angle of puncture line with the horizontal and vertical have significant differences on sex (P < 0.01). The anatomic character of the foramen ovale cranium has important value on the accuracy of puncture for the treatment of trigeminal neuralgia.

Morphological structure of the infraorbital canal using three-dimensional reconstruction.

Our study aim was to evaluate the initial position accurately and the direction of infraorbital canal approximately by analyzing the parameters of infraorbital canal. This study was based on 64-slice computed tomographic multiple planar reconstruction technique and can improve the success rate of infraorbital nerve blockade. The following observations and measurements were carried out in 224 normal infraorbital canals (112 people): the length, angle, and adjoined relations of initial infraorbital canal, to reveal the anatomic characteristics of the canals and to compare the difference between left and right or male and female. Six indicators were measured: (1) the length of initial infraorbital canal; (2) the distance between skin and the first obvious turn of infraorbital canal along the direction of initial infraorbital canal (the depth of puncture); (3) the vertical distance between infraorbital canal and nasal septum; (4) the vertical distance between infraorbital canal and infraorbital rim; (5) the angle between the infraorbital canal and the Frankfort plane; and (6) the angle between the infraorbital canal and the sagittal plane. The difference was statistically significant between 2 sides on the depth of puncture. For other values, the differences between left and right and between women and men were of no statistical significance.

A Noninvasive BCI System for 2D Cursor Control Using a Spectral-Temporal Long Short-Term Memory Network.

Two-dimensional cursor control is an important and challenging problem in the field of electroencephalography (EEG)-based brain computer interfaces (BCIs) applications. However, most BCIs based on categorical outputs are incapable of generating accurate and smooth control trajectories. In this article, a novel EEG decoding framework based on a spectral-temporal long short-term memory (stLSTM) network is proposed to generate control signals in the horizontal and vertical directions for accurate cursor control. Precisely, the spectral information is used to decode the subject's motor imagery intention, and the error-related P300 information is used to detect a deviation in the movement trajectory. The concatenated spectral and temporal features are fed into the stLSTM network and mapped to the velocities in vertical and horizontal directions of the 2D cursor under the velocity-constrained (VC) strategy, which enables the decoding network to fit the velocity in the imaginary direction and simultaneously suppress the velocity in the non-imaginary direction. This proposed framework was validated on a public real BCI control dataset. Results show that compared with the state-of-the-art method, the RMSE of the proposed method in the non-imaginary directions on the testing sets of 2D control tasks is reduced by an average of 63.45%. Besides, the visualization of the actual trajectories distribution of the cursor also demonstrates that the decoupling of velocity is capable of yielding accurate cursor control in complex path tracking tasks and significantly improves the control accuracy.