Clinical effects of traditional Chinese herbal medicine management in patients with COVID-19 sequelae: A hospital-based retrospective cohort study in Taiwan.

Introduction: An estimated 43% of COVID-19 patients showed sequelae, including fatigue, neurocognitive impairment, respiratory symptoms, and smell or taste disorders. These sequelae significantly affect an individual's health, work capacity, healthcare systems, and socioeconomic aspects. Traditional Chinese herbal medicine (TCHM) management showed clinical benefits in treating patients with COVID-19 sequelae. This study aimed to analyze the effects of personalized TCHM management in patients with COVID-19 sequelae. Methods: After the COVID-19 outbreak in Taiwan, we recorded Chronic Obstructive Pulmonary Disease Assessment Tool (CAT), Chalder Fatigue Questionnaire (CFQ-11), and Brief Symptom Rating Scale (BSRS-5) to assess post-COVID respiratory, fatigue, and emotional distress symptoms, respectively. In this study, we retrospectively reviewed the medical records between July 2022 and March 2023. We analyzed the effects of TCHM administration after 14- and 28-days of treatment. Results: 47 patients were included in this study. The results demonstrated that personalized TCHM treatment significantly improved the CAT, CFQ-11, and BSRS-5 scores after 14 and 28 days. TCHM alleviated physical and psychological fatigue. In logistic regression analysis, there was no statistically significant differences in the severity of the baseline symptoms and TCHM administration effects concerning the duration since the initial confirmation of COVID-19, sex, age, or dietary preference (non-vegetarian or vegetarian). Conclusions: Our study suggested that personalized TCHM treatment notably reduced fatigue, respiratory and emotional distress symptoms after 14- and 28-days of treatment in patients with COVID-19 sequelae. We propose that TCHM should be considered as an effective intervention for patients with COVID-19 sequelae.

Time synchronization between parietal-frontocentral connectivity with MRCP and gait in post-stroke bipedal tasks.

BACKGROUND: In post-stroke rehabilitation, functional connectivity (FC), motor-related cortical potential (MRCP), and gait activities are common measures related to recovery outcomes. However, the interrelationship between FC, MRCP, gait activities, and bipedal distinguishability have yet to be investigated. METHODS: Ten participants were equipped with EEG devices and inertial measurement units (IMUs) while performing lower limb motor preparation (MP) and motor execution (ME) tasks. MRCP, FCs, and bipedal distinguishability were extracted from the EEG signals, while the change in knee degree during the ME phase was calculated from the gait data. FCs were analyzed with pairwise Pearson's correlation, and the brain-wide FC was fed into support vector machine (SVM) for bipedal classification. RESULTS: Parietal-frontocentral connectivity (PFCC) dysconnection and MRCP desynchronization were related to the MP and ME phases, respectively. Hemiplegic limb movement exhibited higher PFCC strength than nonhemiplegic limb movement. Bipedal classification had a short-lived peak of 75.1% in the pre-movement phase. These results contribute to a better understanding of the neurophysiological functions during motor tasks, with respect to localized MRCP and nonlocalized FC activities. The difference in PFCCs between both limbs could be a marker to understand the motor function of the brain of post-stroke patients. CONCLUSIONS: In this study, we discovered that PFCCs are temporally dependent on lower limb gait movement and MRCP. The PFCCs are also related to the lower limb motor performance of post-stroke patients. The detection of motor intentions allows the development of bipedal brain-controlled exoskeletons for lower limb active rehabilitation.

Modulating motor cortical oscillation with coordinated reset multifocal transcranial magnetic stimulation.

According to the theory of coordinated reset (CR) stimulation, multifocal bursts of stimuli delivered in a random order with a specific interval may reduce the resonance power of the oscillatory generator in the epicenter. We develop a noninvasive coordinated multifocal burst stimulation (COMBS) with three repetitive transcranial stimulation machines based on CR theory to modulate the target frequency in the primary motor cortex and to assess its effect on motor cortical excitability in separate experiments. Electroencephalography and electromyography were recorded in 16 healthy participants during a finger-tapping task, both before and after the intervention. The resting oscillatory power at the targeted frequency was not changed by COMBS. α-Band power was increased in both preparation and movement stages and the low ß-band power was increased in the movement stage of the finger tapping task. The extent of low ß-band event-related desynchronization was reduced by COMBS. There were no changes in reaction time, but there was a trend for a reduced error rate after COMBS. In another 14 healthy participants, there were no significant changes in cortical excitability before and after COMBS measured by rest motor threshold, short interval intracortical inhibition, short interval intracortical facilitation, and cortical silent period. The result indicates that COMBS may modify the cortical oscillatory power and its perturbation within specific movement stage.NEW & NOTEWORTHY This is the first study, to our knowledge, to apply coordinated reset (CR) neuromodulation to the motor cortex with three repetitive transcranial magnetic stimulation (rTMS) stimulators to assess its effect on cortical oscillation. The results revealed enhancement of α-band power specifically in preparation and movement stages and low ß-band power in the movement stage of a motor task. It postulated that CR stimulation may modify the motor cortical oscillation in the specific movement stages.

Artificial Intelligence Model Trained with Sparse Data to Detect Facial and Cranial Bone Fractures from Head CT.

The presence of cranial and facial bone fractures is an important finding on non-enhanced head computed tomography (CT) scans from patients who have sustained head trauma. Some prior studies have proposed automatic cranial fracture detections, but studies on facial fractures are lacking. We propose a deep learning system to automatically detect both cranial and facial bone fractures. Our system incorporated models consisting of YOLOv4 for one-stage fracture detection and improved ResUNet (ResUNet++) for the segmentation of cranial and facial bones. The results from the two models mapped together provided the location of the fracture and the name of the fractured bone as the final output. The training data for the detection model were the soft tissue algorithm images from a total of 1,447 head CT studies (a total of 16,985 images), and the training data for the segmentation model included 1,538 selected head CT images. The trained models were tested on a test dataset consisting of 192 head CT studies (a total of 5,890 images). The overall performance achieved a sensitivity of 88.66%, a precision of 94.51%, and an F1 score of 0.9149. Specifically, the cranial and facial regions were evaluated and resulted in a sensitivity of 84.78% and 80.77%, a precision of 92.86% and 87.50%, and F1 scores of 0.8864 and 0.8400, respectively. The average accuracy for the segmentation labels concerning all predicted fracture bounding boxes was 80.90%. Our deep learning system could accurately detect cranial and facial bone fractures and identify the fractured bone region simultaneously.

Atypical functional connectivity during rest and task-related dynamic alteration in young children with attention deficit hyperactivity disorder: An analysis using the phase-locking value.

AIM: The study investigated the electroencephalography (EEG) functional connectivity (FC) profiles during rest and tasks of young children with attention deficit hyperactivity disorder (ADHD) and typical development (TD). METHODS: In total, 78 children (aged 5-7 years) were enrolled in this study; 43 of them were diagnosed with ADHD and 35 exhibited TD. Four FC metrics, coherence, phase-locking value (PLV), pairwise phase consistency, and phase lag index, were computed for feature selection to discriminate ADHD from TD. RESULTS: The support vector machine classifier trained by phase-locking value (PLV) features yielded the best performance to differentiate the ADHD from the TD group and was used for further analysis. In comparing PLVs with the TD group at rest, the ADHD group exhibited significantly lower values on left intrahemispheric long interelectrode lower-alpha and beta as well as frontal interhemispheric beta frequency bands. However, the ADHD group showed higher values of central interhemispheric PLVs on the theta, higher-alpha, and beta bands. Regarding PLV alterations within resting and task conditions, left intrahemispheric long interelectrode beta PLVs declined from rest to task in the TD group, but the alterations did not differ in the ADHD group. Negative correlations were observed between frontal interhemispheric beta PLVs and the Disruptive Behavior Disorder Rating Scale as rated by teachers. CONCLUSIONS: These results, which complement the findings of other sparse studies that have investigated task-related brain FC dynamics, particularly in young children with ADHD, can provide clinicians with significant and interpretable neural biomarkers for facilitating the diagnosis of ADHD.

Neural Dynamics of Target Detection via Wireless EEG in Embodied Cognition.

Embodied cognitive attention detection is important for many real-world applications, such as monitoring attention in daily driving and studying. Exploring how the brain and behavior are influenced by visual sensory inputs becomes a major challenge in the real world. The neural activity of embodied mind cognitive states can be understood through simple symbol experimental design. However, searching for a particular target in the real world is more complicated than during a simple symbol experiment in the laboratory setting. Hence, the development of realistic situations for investigating the neural dynamics of subjects during real-world environments is critical. This study designed a novel military-inspired target detection task for investigating the neural activities of performing embodied cognition tasks in the real-world setting. We adopted independent component analysis (ICA) and electroencephalogram (EEG) dipole source localization methods to study the participant's event-related potentials (ERPs), event-related spectral perturbation (ERSP), and power spectral density (PSD) during the target detection task using a wireless EEG system, which is more convenient for real-life use. Behavioral results showed that the response time in the congruent condition (582 ms) was shorter than those in the incongruent (666 ms) and nontarget (863 ms) conditions. Regarding the EEG observation, we observed N200-P300 wave activation in the middle occipital lobe and P300-N500 wave activation in the right frontal lobe and left motor cortex, which are associated with attention ERPs. Furthermore, delta (1-4 Hz) and theta (4-7 Hz) band powers in the right frontal lobe, as well as alpha (8-12 Hz) and beta (13-30 Hz) band powers in the left motor cortex were suppressed, whereas the theta (4-7 Hz) band powers in the middle occipital lobe were increased considerably in the attention task. Experimental results showed that the embodied body function influences human mental states and psychological performance under cognition attention tasks. These neural markers will be also feasible to implement in the real-time brain computer interface. Novel findings in this study can be helpful for humans to further understand the interaction between the brain and behavior in multiple target detection conditions in real life.

Immediate Effect of Whole Body Vibration on Knee Extensor Tendon Stiffness in Hemiparetic Stroke Patients.

Background and Objectives: Whole body vibration is widely used to enhance muscle performance, but evidence of its effects on the tendon stiffness of the knee extensor tendon in stroke remains inconclusive. Our study was aimed to determine the difference in patellar and quadriceps tendon stiffness between hemiparetic and unaffected limbs in stroke patients and to investigate the immediate effect of whole body vibration on tendon stiffness. Materials and Methods: The patellar and quadriceps tendon stiffness of first-ever hemiplegic stroke patients was evaluated with elastography to compare the differences between hemiparetic and unaffected limbs. After one 20 min session of whole body vibration exercise in the standing position, tendon stiffness was again measured to evaluate the immediate effects of whole body vibration on tendon stiffness. Results: The results showed no significant differences in the tendon stiffness of the patellar and quadriceps tendons between hemiparetic and unaffected limbs. However, significant associations were found between the tendon stiffness of the patellar and quadriceps tendons and knee extensor spasticity on the hemiparetic side (ρ = 0.62; p = 0.044). There were no significant changes in tendon stiffness after a single session of whole body vibration. Conclusions: In conclusion, knee extensor tendon stiffness in hemiparetic limbs is positively correlated to the degree of knee extensor spasticity in stroke patients. However, a single session of whole body vibration does not alter tendon stiffness.

Exploration of Brain Connectivity during Human Inhibitory Control Using Inter-Trial Coherence.

Inhibitory control is a cognitive process that inhibits a response. It is used in everyday activities, such as driving a motorcycle, driving a car and playing a game. The effect of this process can be compared to the red traffic light in the real world. In this study, we investigated brain connectivity under human inhibitory control using the phase lag index and inter-trial coherence (ITC). The human brain connectivity gives a more accurate representation of the functional neural network. Results of electroencephalography (EEG), the data sets were generated from twelve healthy subjects during left and right hand inhibitions using the auditory stop-signal task, showed that the inter-trial coherence in delta (1-4 Hz) and theta (4-7 Hz) band powers increased over the frontal and temporal lobe of the brain. These EEG delta and theta band activities neural markers have been related to human inhibition in the frontal lobe. In addition, inter-trial coherence in the delta-theta and alpha (8-12 Hz) band powers increased at the occipital lobe through visual stimulation. Moreover, the highest brain connectivity was observed under inhibitory control in the frontal lobe between F3-F4 channels compared to temporal and occipital lobes. The greater EEG coherence and phase lag index in the frontal lobe is associated with the human response inhibition. These findings revealed new insights to understand the neural network of brain connectivity and underlying mechanisms during human response inhibition.

Exploration of User's Mental State Changes during Performing Brain-Computer Interface.

Substantial developments have been established in the past few years for enhancing the performance of brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP). The past SSVEP-BCI studies utilized different target frequencies with flashing stimuli in many different applications. However, it is not easy to recognize user's mental state changes when performing the SSVEP-BCI task. What we could observe was the increasing EEG power of the target frequency from the user's visual area. BCI user's cognitive state changes, especially in mental focus state or lost-in-thought state, will affect the BCI performance in sustained usage of SSVEP. Therefore, how to differentiate BCI users' physiological state through exploring their neural activities changes while performing SSVEP is a key technology for enhancing the BCI performance. In this study, we designed a new BCI experiment which combined working memory task into the flashing targets of SSVEP task using 12 Hz or 30 Hz frequencies. Through exploring the EEG activity changes corresponding to the working memory and SSVEP task performance, we can recognize if the user's cognitive state is in mental focus or lost-in-thought. Experiment results show that the delta (1-4 Hz), theta (4-7 Hz), and beta (13-30 Hz) EEG activities increased more in mental focus than in lost-in-thought state at the frontal lobe. In addition, the powers of the delta (1-4 Hz), alpha (8-12 Hz), and beta (13-30 Hz) bands increased more in mental focus in comparison with the lost-in-thought state at the occipital lobe. In addition, the average classification performance across subjects for the KNN and the Bayesian network classifiers were observed as 77% to 80%. These results show how mental state changes affect the performance of BCI users. In this work, we developed a new scenario to recognize the user's cognitive state during performing BCI tasks. These findings can be used as the novel neural markers in future BCI developments.

Neural Activities Classification of Human Inhibitory Control Using Hierarchical Model.

Human inhibitory control refers to the suppression of behavioral response in real environments, such as when driving a car or riding a motorcycle, playing a game and operating a machine. The P300 wave is a neural marker of human inhibitory control, and it can be used to recognize the symptoms of attention deficit hyperactivity disorder (ADHD) in human. In addition, the P300 neural marker can be considered as a stop command in the brain-computer interface (BCI) technologies. Therefore, the present study of electroencephalography (EEG) recognizes the mindset of human inhibition by observing the brain dynamics, like P300 wave in the frontal lobe, supplementary motor area, and in the right temporoparietal junction of the brain, all of them have been associated with response inhibition. Our work developed a hierarchical classification model to identify the neural activities of human inhibition. To accomplish this goal phase-locking value (PLV) method was used to select coupled brain regions related to inhibition because this method has demonstrated the best performance of the classification system. The PLVs were used with pattern recognition algorithms to classify a successful-stop versus a failed-stop in left-and right-hand inhibitions. The results demonstrate that quadratic discriminant analysis (QDA) yielded an average classification accuracy of 94.44%. These findings implicate the neural activities of human inhibition can be utilized as a stop command in BCI technologies, as well as to identify the symptoms of ADHD patients in clinical research.

Development of a Smart Helmet for Strategical BCI Applications.

Conducting electrophysiological measurements from human brain function provides a medium for sending commands and messages to the external world, as known as a brain-computer interface (BCI). In this study, we proposed a smart helmet which integrated the novel hygroscopic sponge electrodes and a combat helmet for BCI applications; with the smart helmet, soldiers can carry out extra tasks according to their intentions, i.e., through BCI techniques. There are several existing BCI methods which are distinct from each other; however, mutual issues exist regarding comfort and user acceptability when utilizing such BCI techniques in practical applications; one of the main challenges is the trade-off between using wet and dry electroencephalographic (EEG) electrodes. Recently, several dry EEG electrodes without the necessity of conductive gel have been developed for EEG data collection. Although the gel was claimed to be unnecessary, high contact impedance and low signal-to-noise ratio of dry EEG electrodes have turned out to be the main limitations. In this study, a smart helmet with novel hygroscopic sponge electrodes is developed and investigated for long-term usage of EEG data collection. The existing electrodes and EEG equipment regarding BCI applications were adopted to examine the proposed electrode. In the impedance test of a variety of electrodes, the sponge electrode showed performance averaging 118 kΩ, which was comparable with the best one among existing dry electrodes, which averaged 123 kΩ. The signals acquired from the sponge electrodes and the classic wet electrodes were analyzed with correlation analysis to study the effectiveness. The results indicated that the signals were similar to each other with an average correlation of 90.03% and 82.56% in two-second and ten-second temporal resolutions, respectively, and 97.18% in frequency responses. Furthermore, by applying the proposed differentiable power algorithm to the system, the average accuracy of 21 subjects can reach 91.11% in the steady-state visually evoked potential (SSVEP)-based BCI application regarding a simulated military mission. To sum up, the smart helmet is capable of assisting the soldiers to execute instructions with SSVEP-based BCI when their hands are not available and is a reliable piece of equipment for strategical applications.

Glycoprotein B7-H3 overexpression and aberrant glycosylation in oral cancer and immune response.

The incidence and mortality rate of oral cancer continue to rise, partly due to the lack of effective early diagnosis and increasing environmental exposure to cancer-causing agents. To identify new markers for oral cancer, we used a sialylation probe to investigate the glycoproteins differentially expressed on oral cancer cells. Of the glycoproteins identified, B7 Homolog 3 (B7-H3) was significantly overexpressed in oral squamous cell carcinoma (OSCC), and its overexpression correlated with larger tumor size, advanced clinical stage, and low survival rate in OSCC patients. In addition, knockdown of B7-H3 suppressed tumor cell proliferation, and restoration of B7-H3 expression enhanced tumor growth. It was also found that the N-glycans of B7-H3 from Ca9-22 oral cancer cells contain the terminal α-galactose and are more diverse with higher fucosylation and better interaction with DC-SIGN [DC-specific intercellular adhesion molecule-3 (ICAM-3)-grabbing nonintegrin] and Langerin on immune cells than that from normal cells, suggesting that the glycans on B7-H3 may also play an important role in the disease.

Naringenin attenuates hepatitis B virus X protein-induced hepatic steatosis.

BACKGROUND: Naringenin (Nar), a common dietary flavonoid abundantly present in fruits, vegetables, and Chinese herbs, is believed to possess strong anti-inflammatory properties and to modulate hepatic apolipoprotein and lipid synthesis. However, there are no reports describing Nar's effects on the hepatitis B virus protein X (HBx) -induced hepatic steatosis, and the detailed molecular mechanisms of the compound's effects are still unclear. METHODS: Nar was administered by oral gavage to HBx-transgenic mice from 4 to 6 weeks of age. Mice were sacrificed after 14 days of once-daily naringenin administration. Liver tissues and sera were collected for histopathology and biochemical analysis. RESULTS: Nar counteracted hepatic lipid accumulation and liver dysfunction in HBx-transgenic mice. In addition, Nar significantly decreased expression of adipogenic and lipogenic genes in mice, suggesting that the compound may have therapeutic effects in the early stages of HBx-mediated hepatic steatosis. These results indicated that naringenin inhibits HBx-induced expression of hepatic adipogenic and lipogenic genes through suppression of HBx-induced gene expression, including decreases in the transcriptional activity of SREBP1c, LXRα, and PPARγ in HBx-trangenic mice and HBx-transfected HepG2 cells. CONCLUSIONS: Results from this study suggested that Nar may serve as a therapeutic agent for preventing HBx-infected hepatic steatosis in humans.

CDK2 phosphorylation regulates the protein stability of KLF10 by interfering with binding of the E3 ligase SIAH1.

Downregulation of multiple cell cycle-regulatory molecules is a dominant event in TGF-ß1-mediated growth inhibition of human carcinoma cells. It is known that KLF10 mimics the anti-proliferative and apoptotic effects that TGF-ß1 has on epithelial cell growth and the growth of various tumor cells; based on these findings it is considered as a tumor suppressor. KLF10 protein expression is tightly associated with cell cycle-dependent events. However, the regulatory mechanism and its biological meaning have not been identified. In this study, we have demonstrated that KLF10 is a substrate of CDK2/cyclin E and can be phosphorylated. We also have shown that KLF10 efficiently binds to CDK2, while binding much less to CDK4, and displaying no binding to Cdk6. Using mass spectrometry, site direct mutagenesis, in vitro kinase assays and depletion assays, we have established that CDK2 phosphorylates Ser206, which subsequently affects the steady state level of KLF10 in cells. Our studies have also proved that CDK2 up-regulates the protein level of KLF10 through reducing its association with SIAH1, a KLF10 E3-ubiqutin ligase involved in proteasomal degradation. Taken all together, these findings indicate that CDK2-dependent phosphorylation regulates KLF10 stability and that this affects the role of KLF10 in cell.

Kinesthesia in a sustained-attention driving task.

This study investigated the effects of kinesthetic stimuli on brain activities during a sustained-attention task in an immersive driving simulator. Tonic and phasic brain responses on multiple timescales were analyzed using time-frequency analysis of electroencephalographic (EEG) sources identified by independent component analysis (ICA). Sorting EEG spectra with respect to reaction times (RT) to randomly introduced lane-departure events revealed distinct effects of kinesthetic stimuli on the brain under different performance levels. Experimental results indicated that EEG spectral dynamics highly correlated with performance lapses when driving involved kinesthetic feedback. Furthermore, in the realistic environment involving both visual and kinesthetic feedback, a transitive relationship of power spectra between optimal-, suboptimal-, and poor-performance groups was found predominately across most of the independent components. In contrast to the static environment with visual input only, kinesthetic feedback reduced theta-power augmentation in the central and frontal components when preparing for action and error monitoring, while strengthening alpha suppression in the central component while steering the wheel. In terms of behavior, subjects tended to have a short response time to process unexpected events with the assistance of kinesthesia, yet only when their performance was optimal. Decrease in attentional demand, facilitated by kinesthetic feedback, eventually significantly increased the reaction time in the suboptimal-performance state. Neurophysiological evidence of mutual relationships between behavioral performance and neurocognition in complex task paradigms and experimental environments, presented in this study, might elucidate our understanding of distributed brain dynamics, supporting natural human cognition and complex coordinated, multi-joint naturalistic behavior, and lead to improved understanding of brain-behavior relations in operating environments.

Single-incision versus conventional laparoscopic appendectomy in 688 patients: a retrospective comparative analysis.

BACKGROUND: Laparoscopic surgery has become the standard for treating appendicitis. The cosmetic benefits of using single-incision laparoscopy are well known, but its duration, complications and time to recovery have not been well documented. We compared 2 laparoscopic approaches for treating appendicitis and evaluated postoperative pain, complications and time to full recovery. METHODS: We retrospectively reviewed the cases of consecutive patients with appendicitis and compared those who underwent conventional laparoscopic appendectomy (CLA) performed using 3 incisions and those who underwent single-incision laparoscopic appendectomy (SILA). During SILA, the single port was prepared to increase visibility of the operative site. RESULTS: Our analysis included 688 consecutive patients: 618 who underwent CLA and 70 who underwent SILA. Postsurgical complications occurred more frequently in the CLA than the SILA group (18.1% v. 7.1%, p = 0.018). Patients who underwent SILA returned to oral feeding sooner than those who underwent CLA (median 12 h v. 22 h, p < 0.001). These between-group differences remained significant after controlling for other factors. Direct comparison of only nonperforated cases, which was determined by pathological examination, revealed that SILA was significantly longer than CLA (60 min v. 50 min, p < 0.001). Patients who underwent SILA had longer in-hospital stays than those who underwent CLA (72 v. 55 h, p < 0.001); however, they had significantly fewer complications (3.0% v. 14.4%, p = 0.006). CONCLUSION: In addition to its cosmetic advantages, SILA led to rapid recovery and no increase in postsurgical pain or complications.

CONTEXTE: La chirurgie laparoscopique est devenue la norme pour le traitement de l'appendicite. Les avantages de la laparoscopie à simple incision au plan esthétique sont bien connus, mais la durée de l'intervention, ses complications et le temps de récupération n'ont pas été adéquatement documentés. Nous avons comparé 2 approches laparoscopiques pour le traitement de l'appendicite et évalué la douleur et les complications postopératoires, de même que le temps de récupération complète. MÉTHODES: Nous avons passé en revue de manière rétrospective les dossiers de patients consécutifs atteints d'appendicite et comparé ceux qui ont subi une appendicectomie laparoscopique classique (ALC) à 3 incisions à ceux qui ont subi une appendicectomie laparoscopique à simple incision (ALSI). Durant l'ALSI, l'incision était préparée de manière à améliorer la visibilité du champ opératoire. RÉSULTATS: Notre analyse a inclus 688 patients consécutifs : 618 qui ont subi une ALC et 70, une ALSI. Les complications postopératoires ont été plus nombreuses dans le groupe soumis à l'ALC qu'à l'ALSI (18,1 % c. 7,1 %, p = 0,018). Les patients soumis à l'ALSI ont repris l'alimentation orale plus rapidement que ceux qui avaient subi une ALC (temps médian 12 h c. 22 h, p < 0,001). Ces différences entre les groupes sont demeurées significatives après incorporation d'autres facteurs. La comparaison directe des cas non perforés seulement, révélés par l'examen anatomopathologique, a révélé que l'ALSI a demandé significativement plus de temps que l'ALC (60 min c. 50 min, p < 0,001). Les patients soumis à l'ALSI ont séjourné plus longtemps à l'hôpital que les patients soumis à l'ALC (72 h c. 55 h, p < 0,001); toutefois, ils ont présenté significativement moins de complications (3,0 % c. 14,4 %, p = 0,006). CONCLUSION: En plus de ses avantages au plan esthétique, l'ALSI a permis une récupération rapide, sans accroissement de la douleur ou des complications postopératoires.

Temporal Alpha Dissimilarity of ADHD Brain Network in Comparison With CPT and CATA.

Attention deficit hyperactivity disorder (ADHD) is a chronic neurological and psychiatric disorder that affects children during their development. To find neural patterns for ADHD and provide subjective features as decision references to assist specialists and physicians. Many studies have been devoted to investigating the neural dynamics of the brain through resting-state or continuous performance tests (CPT) with EEG or functional magnetic resonance imaging (fMRI). The present study used coherence, which is one of the functional connectivity (FC) methods, to analyze the neural patterns of children and adolescents (8-16 years old) under CPT and continuous auditory test of attention (CATA) task. In the meantime, electroencephalography (EEG) oscillations were recorded by a wireless brain-computer interface (BCI). 72 children were enrolled, of which 53 participants were diagnosed with ADHD and 19 presented to be typical developing (TD). The experimental results exhibited a higher difference in alpha and theta bands between the TD group and the ADHD group. While the differences between the TD group and the ADHD group in all four frequency domains were greater than under CPT conditions. Statistically significant differences ( [Formula: see text]) were observed between the ADHD and TD groups in the alpha rhythm during the CATA task in the short-range of coherence. For the temporal lobe FC during the CATA task, the TD group exhibited statistically significantly FC ( [Formula: see text]) in the alpha rhythm compared to the ADHD group. These findings offering new possibilities for more techniques and diagnostic methods in finding more ADHD features. The differences in alpha and beta frequencies were more pronounced in the ADHD group during the CPT task compared to the CATA task. Additionally, the disparities in brain activity were more evident across delta, theta, alpha and beta frequency domains when the task given was a CATA as opposed to a CPT. The findings presented the underlying mechanisms of the FC differences between children and adolescents with ADHD. Moreover, these findings should extend to use machine learning approaches to assist the ADHD classification and diagnosis.

Successful Recanalization and Neurological Restoration in Cancerous Embolic Cerebral Infarction via Endovascular Stent-Retriever Embolectomy.

Mechanical thrombectomy has emerged as a promising treatment for acute ischemic stroke caused by large vessel occlusion. However, cases involving cancerous emboli retrieved during endovascular embolectomy are rare. We present a case of a 65-year-old man with a history of heavily treated rectal cancer, who developed a middle cerebral artery (MCA) infarction due to metastatic adenocarcinoma. The patient presented with sudden onset right-side weakness, right facial palsy, global aphasia, and left gaze deviation, with a National Institutes of Health Stroke Scale (NIHSS) score of 16. Following intravenous thrombolysis, endovascular thrombectomy was performed, achieving nearly complete recanalization. Pathological examination of the retrieved thrombus revealed metastatic adenocarcinoma of rectal origin. The patient's neurological deficits gradually improved, and he was successfully discharged to undergo further palliative therapy. This case underscores the importance of considering mechanical thrombectomy for patients with advanced solid organ malignancy presenting with acute ischemic stroke, even when the etiology could be a tumor embolus. Our findings highlight the potential for mechanical thrombectomy to restore neurological function in such cases, allowing patients to proceed to the next level of care with a reasonably good post-stroke quality of life.

Electrophysiological functional connectivity and complexity reflecting cognitive processing speed heterogeneity in young children with ADHD.

Early intervention is imperative for young children with attention-deficit/hyperactivity disorder (ADHD) who manifest heterogeneous neurocognitive deficits. The study investigated the functional connectivity and complexity of brain activity among young children with ADHD exhibiting a fast cognitive processing speed (ADHD-F, n = 26), with ADHD exhibiting a slow cognitive processing speed (ADHD-S, n = 17), and typically developing children (n = 35) using wireless electroencephalography (EEG) during rest and task conditions. During rest, compared with the typically developing group, the ADHD-F group displayed lower long-range intra-hemispheric connectivity, while the ADHD-S group had lower frontal beta inter-hemispheric connectivity. During task performance, the ADHD-S group displayed lower frontal beta inter-hemispheric connectivity than the typically developing group. The ADHD-S group had lower frontal inter-hemispheric connectivity in broader frequency bands than the ADHD-F group, indicating ADHD heterogeneity in mental processing speed. Regarding complexity, the ADHD-S group tended to show lower frontal entropy estimators than the typically developing group during the task condition. These findings suggest that the EEG profile of brain connectivity and complexity can aid the early clinical diagnosis of ADHD, support subgrouping young children with ADHD based on cognitive processing speed heterogeneity, and may contain specific novel neural biomarkers for early intervention planning.

Extracting Stress-Related EEG Patterns From Pre-Sleep EEG for Forecasting Slow-Wave Sleep Deficiency.

Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall health. While stress is known for its detrimental impact on sleep quality, the precise effect of pre-sleep stress on subsequent sleep structure remains unknown. This study introduced a novel approach to study the pre-sleep stress effect on sleep structure, specifically slow-wave sleep (SWS) deficiency. To achieve this, we selected forehead resting EEG immediately before and upon sleep onset to extract stress-related neurological markers through power spectra and entropy analysis. These markers include beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn) and spectral entropy (SpEn). Fifteen subjects were included in this study. Our results showed that subjects lacking SWS often exhibited signs of stress in EEG, such as an increased beta/delta correlation, higher alpha asymmetry, and increased FuzzEn in frontal EEG. Conversely, individuals with ample SWS displayed a weak beta/delta correlation and reduced FuzzEn. Finally, we employed several supervised learning models and found that the selected neurological markers can predict subsequent SWS deficiency. Our investigation demonstrated that the classifiers could effectively predict varying levels of slow-wave sleep (SWS) from pre-sleep EEG segments, achieving a mean balanced accuracy surpassing 0.75. The SMOTE-Tomek resampling method could improve the performance to 0.77. This study suggests that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. Such information can be integrated with existing sleep-improving techniques to provide a personalized sleep forecasting and improvement solution.