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Ziwen Wang,1,2 Jiaxuan Fang,1,2 Shigao Zu,1,2 Qianru Sun,1,2 Zixin Song,1,2 Jiman Geng,1,2 Dongdong Wang,1,2 Meng Li,1,2 Changtao Wang1,2 1Beijing Key Laboratory of Plant Resource Research and Development, Beijing Technology and Business University, Beijing, 100048, People’s Republic of China; 2School of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, People’s Republic of ChinaCorrespondence: Dongdong Wang; Changtao Wang, Beijing Technology and Business University, Beijing, 100048, People’s Republic of China, Tel/Fax +86 158 1135 7756, Email wdd@btbu.edu.cn; wangct@th.btbu.edu.cnPurpose: To produce Panax notoginseng extract as a cosmetic ingredient through Saccharomyces cerevisiae fermentation.Methods: We first compared the total sugar content, polysaccharide content, reducing sugar content, total phenolic content, total saponin content, DPPH free radical, ABTS free radical, hydroxyl free radical scavenging ability and ferric reducing antioxidant power (FRAP) of Panax notoginseng fermented extract (pnFE) and unfermented extract (pnWE). Their potential correlations were analyzed by Pearson’s correlation analysis. Then, the oxidative stress model of H2O2-induced MSFs was used to evaluate the effects of different pnFE on MSF viability, reactive oxygen species (ROS), malondialdehyde (MDA), and the activities of catalase (CAT), glutathione peroxidase (GSH-Px) and superoxide dismutase (SOD) to explore their protective effects on MSFs subjected to H2O2-induced cellular oxidative damage. Finally, their safety and stability were evaluated by using the red blood cell (RBC) test and hen’s egg test-chorioallantoic membrane (HET-CAM) assay, and changes in pH and content of soluble solids, respectively.Results: Compared with pnWE, pnFE has more active substances and stronger antioxidant capacity. In addition, pnFE has a protective effect on H2O2-induced oxidative stress in MSFs with appropriate safety and stability.Conclusion: PnFE has broad application prospects in the field of cosmetics.Keywords: Panax notoginseng, Saccharomyces cerevisiae, fermentation, oxidative stress, fibroblast cells, cosmetic ingredients

Yumin Ke,1,* Shuiling Zu,2,* Lijun Chen,3,* Meizhi Liu,4 Haijun Yang,5 Fuqiang Wang,5 Huanhuan Zheng,6 Fangjie He7,8 1Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, People’s Republic of China; 2Nursing Department, The Third Affiliated People’s Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, 350100, People’s Republic of China; 3Department of Gynecological Oncology, Fujian Cancer Hospital, Fujian Medical University Cancer Hospital, Fuzhou, 350014, People’s Republic of China; 4Department of Gynecology, The Third Affiliated People’s Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, 350100, People’s Republic of China; 5Department of Pathology, The Anyang Tumor Hospital, Anyang, 455000, People’s Republic of China; 6Department of Endocrinology, Ji’an Central People’s Hospital, Ji’an, 343000, People’s Republic of China; 7Department of Obstetrics and Gynecology, The First People’s Hospital of Foshan, Foshan, 528000, People’s Republic of China; 8State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, 510060, People’s Republic of China*These authors contributed equally to this workCorrespondence: Fangjie HeDepartment of Obstetrics and Gynecology, The First People’s Hospital of Foshan, Foshan, People’s Republic of China; State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, 510060, People’s Republic of China, Tel +86-18038864533, Fax +86 757-83162610, Email hfj5362@fsyyy.com; dr_hefangjie@163.comObjective: This study aimed to identify a subset of patients with stage IA2 to IIA2 cervical cancer who are at low risk of lymph node metastasis (LNM) using pathological parameters including estrogen receptor alpha (ERα) and progesterone receptor (PR).Methods: The clinical data of patients with stage IA2 to IIA2 cervical cancer who underwent radical surgery between 2014 and 2015 were retrospectively reviewed. Immunohistochemical staining was used to determine the expression of ERα and PR. A low-risk criterion for LNM was identified using logistic regression analysis, and its performance was estimated through receiver-operating characteristic curve analysis.Results: Of 263 patients, 57 (21.7%) had pathological LNM. ERα (adjusted odds ratio [aOR], 7.582; 95% confidence interval [CI], 2.991– 19.222; P < 0.001) and squamous cell carcinoma (aOR, 3.520; 95% CI, 1.887– 6.568; P < 0.001) were identified as independent predictors for no LNM by multivariate logistic regression analysis, while PR had no effect on LNM. The rate of LNM was 1.4% for low-risk patients (n = 73) identified as ERα positive with squamous cell carcinoma. The 5-year disease-free survival in low-risk patients was significantly greater than in those negative for ERα and/or those with non-squamous cell carcinoma (96.9% vs 80.1%, P = 0.002).Conclusion: ERα positivity and squamous cell carcinoma are associated with a low risk of LNM in patients with stage IA2 to IIA2 cervical cancer. Hence, those patients without a low risk of LNM could be considered for definitive chemoradiotherapy to avoid unnecessary surgery.Keywords: cervical cancer, lymph node, estrogen receptor alpha, progesterone receptor, squamous cell carcinoma

Si Zu,1 Dong Wang,1 Jiexin Fang,1 Le Xiao,2 Xuequan Zhu,2 Wenyuan Wu,3 Gang Wang,2,4 Yongdong Hu1 1Department of Psychiatry, Beijing Chaoyang Hospital, Capital Medical University, Beijing, People’s Republic of China; 2The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China; 3Department of Psychiatry, Tongji Hospital of Tongji University, Shanghai, People’s Republic of China; 4Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of ChinaCorrespondence: Gang WangThe National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, No. 5 Ankang Lane, Xicheng District, Beijing Anding Hospital, Beijing, 100088, People’s Republic of ChinaEmail gangwangdoc@ccmu.edu.cnYongdong HuDepartment of Psychiatry, Beijing Chaoyang Hospital, Capital Medical University, No. 8 Gongtinanlu, Chaoyang District, Beijing Chaoyang Hospital, Beijing, 100020, People’s Republic of ChinaTel +86-10-85231754Email haiyong.xie@ustc.eduObjective: This prospective study aimed to investigate the prognosis and rehabilitation of patients with recurrent depression and first episode depression after acute treatment in China.Methods: A total of 434 patients with first-episode or recurrent depression who received acute treatment respectively from sixteen hospitals in thirteen cities in China were enrolled in this prospective study. All patients were followed up for 6 months after acute treatment. The following data were collected at baseline period and 1, 3, and 6 months after acute treatment: general information of patients, medication information and patient’s condition changes, brief 16-item quick inventory of depressive symptomatology self-report (QIDS-SR16), patient health questionnaire-15 (PHQ-15), quality of life enjoyment and satisfaction questionnaire-short form (Q-LES-Q-SF), Sheehan disability scale (SDS) and digit symbol substitution test (DSST).Results: During the baseline period, there was a significant difference in QIDS-SR16 between recurrent patients and first-episode patients (p < 0.05), and there was no significant difference in other indicators (p > 0.05). At one month after acute treatment, there were significant differences in the total QIDS-SR16 score, the total Q-LES-SF score, the social life score, and the family life/home responsibilities score of SDS in patients with recurrent depression and first-episode depression (p < 0.05). At three months after acute treatment, there were significant differences in the total Q-LES-SF score and social life score of SDS in patients with recurrent depression and first-episode depression (p < 0.05). At six months after acute treatment, there were significant differences in the total QIDS-SR16 score, the social life score, and the total Q-LES-SF score in patients with recurrent depression and first-episode depression (p < 0.05). Compared with that data during the baseline period, the QIDS-SR16 scores and the SDS scores of all patients decreased, and the Q-LES-SF scores of all patients gradually increased as time went on during the consolidation period.Conclusion: The recurrent patients have more severe social function impairment, depressive symptoms, and lower life quality than that of the first-episode depressed patients. Given the negative impact of depressed symptom on recurrent patient, more attention should be paid to the treatment of recurrent patient and recurrence prevention of first episode patient.Keywords: depression, first-episode, recurrent patient, prognosis

Yuangang Zu, Qi Zhao, Xiuhua Zhao, Shuchong Zu, Li MengKey Laboratory of Forest Plant Ecology, Northeast Forestry University, Ministry of Education, Harbin, Heilongjiang, ChinaAbstract: Oligomycin-A (Oli-A), an anticancer drug, was loaded to the folate (FA)-conjugated chitosan as a tumor-targeted drug delivery system for the purpose of overcoming the nonspecific targeting characteristics and the hydrophobicity of the compound. The two-level factorial design (2-LFD) was applied to modeling the preparation process, which was composed of five independent variables, namely FA-conjugated chitosan (FA-CS) concentration, Oli-A concentration, sodium tripolyphosphate (TPP) concentration, the mass ratio of FA-CS to TPP, and crosslinking time. The mean particle size (MPS) and the drug loading rate (DLR) of the resulting Oli-loaded FA-CS nanoparticles (FA-Oli-CSNPs) were used as response variables. The interactive effects of the five independent variables on the response variables were studied. The characteristics of the nanoparticles, such as amount of FA conjugation, drug entrapment rate (DER), DLR, surface morphology, and release kinetics properties in vitro were investigated. The FA-Oli-CSNPs with MPS of 182.6 nm, DER of 17.3%, DLR of 58.5%, and zeta potential (ZP) of 24.6 mV were obtained under optimum conditions. The amount of FA conjugation was 45.9 mg/g chitosan. The FA-Oli-CSNPs showed sustained-release characteristics for 576 hours in vitro. The results indicated that FA-Oli-CSNPs obtained as a targeted drug delivery system could be effective in the therapy of leukemia in the future.Keywords: oligomycin-A, chitosan, folate, targeted drug delivery system, nanoparticles, two-level factorial design

We investigated a newly developed digitized Trail Making Test using an iPad (iTMT) as a brief cognitive function screening test. We found that the iTMT part-A (iTMT-A) can estimate generalized cognitive function in rehabilitation inpatients examined using the Mini-Mental State Examination (MMSE). Forty-two hospitalized participants undergoing rehabilitation (rehab participants), 30 of whom had cerebral infarction/hemorrhage (stroke participants), performed the iTMT five times (first three times: iTMT-A; fourth: paper version of TMT-A; fifth: the inverse version of iTMT-A) and the MMSE once. Each iTMT-A trial's completion time was divided into the move and dwell times. A linear mixed model following post-hoc tests revealed that the completion time of the third and fourth iTMT-A was faster compared to that of the first iTMT-A, suggesting the presence of a learning effect. In the partial least squares (PLS) regression analysis, the coefficient of determination for estimating the MMSE score was increased by using the dwell and move times extracted from the repeated iTMT-A and the availability of TMT-B, even for subjects with low MMSE scores. These findings indicate that the dwell time of iTMT-A may be important for estimating cognitive function. The iTMT-A extracts significant factors temporally and spatially, and by incorporating the learning effect of repeated trials, it may be possible to screen cognitive and physical functions for rehabilitation patients.

Abstract Anticipation of pain engenders anxiety and fear, potentially shaping pain perception and governing bodily responses such as peripheral vasomotion through the sympathetic nervous system (SNS). Sympathetic innervation of vascular tone during pain perception has been quantified using a peripheral arterial stiffness index; however, its innervation role during pain anticipation remains unclear. This paper reports on a neuroimaging-based study designed to investigate the responsivity and attribution of the index at different levels of anticipatory anxiety and pain perception. The index was measured in a functional magnetic resonance imaging experiment that randomly combined three visual anticipation cues and painful stimuli of two intensities. The peripheral and cerebral responses to pain anticipation and perception were quantified to corroborate bodily responsivity, and their temporal correlation was also assessed to identify the response attribution of the index. Contrasting with the high responsivity across levels of pain sensation, a low responsivity of the index across levels of anticipatory anxiety revealed its specificity across pain experiences. Discrepancies between the effects of perception and anticipation were validated across regions and levels of brain activity, providing a brain basis for peripheral response specificity. The index was also characterized by a 1-s lag in both anticipation and perception of pain, implying top-down innervation of the periphery. Our findings suggest that the SNS responds to pain in an emotion-specific and sensation-unbiased manner, thus enabling an early assessment of individual pain perception using this index. This study integrates peripheral and cerebral hemodynamic responses toward a comprehensive understanding of bodily responses to pain.

Goal: Microbubbles (MBs) are known to occur within the circuits of cardiopulmonary bypass (CPB) systems, and higher-order dysfunction after cardiac surgery may be caused by MBs as well as atheroma dispersal associated with cannula insertion. As complete MB elimination is not possible, monitoring MB count rates is critical. We propose an online detection system with a neural network-based model to estimate MB count rate using five parameters: suction flow rate, venous reservoir level, perfusion flow rate, hematocrit level, and blood temperature. Methods: Perfusion experiments were performed using an actual CPB circuit, and MB count rates were measured using the five varying parameters. Results: Bland–Altman analysis indicated a high estimation accuracy (R2 > 0.95, p < 0.001) with no significant systematic error. In clinical practice, although the inclusion of clinical procedures slightly decreased the estimation accuracy, a high coefficient of determination for 30 clinical cases (R2 = 0.8576) was achieved between measured and estimated MB count rates. Conclusions: Our results highlight the potential of this system to improve patient outcomes and reduce MB-associated complication risk.

By confining light into a deep subwavelength scale to match the characteristic dimension of quantum emitters, plasmonic nanocavities can effectively imprint the light emission with unique properties in terms of intensity, directionality, as well as polarization. In this vein, achiral quantum emitters can generate chiral photons through coupling with plasmonic nanocavities with either intrinsic or extrinsic chirality. As an important metric for the chiral-photon purity, the degree of circular polarization (DCP) is usually tuned by various scattered factors such as the nanocavity design, the emitter type, and the coupling strategy. The physical mechanisms of the chiral photon generation, especially when plasmons and emitters step into the strong coupling regime, are less explored. In this paper, we extended the coupled-oscillator and Jaynes–Cummings models to their chiral fashion to account for the above factors within a single theoretical framework and investigated the chiroptical properties of a plasmonic nanocavity-emitter hybrid system from weak to strong coupling. It was demonstrated that both the circular differential scattering and prominent scattering DCP rely on the intrinsic chirality generated by breaking the mirror symmetry with the emitter, and is thereby tunable by the coupling strength. However, the luminescence DCP (as high as 87 %) is closely related to the extrinsic chirality of the bare nanocavity and independent of the coupling strength. The results thus reveal two different physical mechanisms of generating chiral photons in scattering and luminescence. Our findings provide a theoretical guideline for designing chiral photon devices and contribute to the understanding of chiral plasmon-emitter interaction.

Abstract Dynamic visual acuity (DVA) is crucial for the perception of moving objects. While traditional DVA assessment tools predominantly focus on horizontal movements, the evaluation of vertical DVA remains unstandardized. Consequently, the disparities between vertical and horizontal DVAs are yet to be thoroughly investigated. Therefore, we designed a system capable of conducting multidirectional DVA tests and eye movement measurements. During the experiments, the participants identified the gap direction of the Landolt-C ring moving either horizontally or vertically. The speed of movement decelerated from its maximum as a high-speed infrared camera captured the pupil movements of the left eye at 500 fps. We conducted tests on 15 healthy university students (aged $$22.7\pm 1.2$$ 22.7 ± 1.2 years) and measured vertical and horizontal DVAs five times each. DVA was deduced from the Landolt-C ring speed with accurate gap direction responses, and eye movement was assessed based on the total gaze movement distance. The results revealed superior DVA and eye movement in the horizontal direction compared with the vertical direction ( $$p < 0.001$$ p < 0.001 ). This highlights the anisotropic characteristics of DVA and eye movement. The proposed system has the potential for multidirectional dynamic vision evaluation and training in clinical scenarios.

Abstract Background People who were previously hospitalised with stroke may have difficulty operating a motor vehicle, and their driving aptitude needs to be evaluated to prevent traffic accidents in today’s car-based society. Although the association between motor-cognitive functions and driving aptitude has been extensively studied, motor-cognitive functions required for driving have not been elucidated. Methods In this paper, we propose a machine-learning algorithm that introduces sparse regularization to automatically select driving aptitude-related indices from 65 input indices obtained from 10 tests of motor-cognitive function conducted on 55 participants with stroke. Indices related to driving aptitude and their required tests can be identified based on the output probability of the presence or absence of driving aptitude to provide evidence for identifying subjects who must undergo the on-road driving test. We also analyzed the importance of the indices of motor-cognitive function tests in evaluating driving aptitude to further clarify the relationship between motor-cognitive function and driving aptitude. Results The experimental results showed that the proposed method achieved predictive evaluation of the presence or absence of driving aptitude with high accuracy (area under curve 0.946) and identified a group of indices of motor-cognitive function tests that are strongly related to driving aptitude. Conclusions The proposed method is able to effectively and accurately unravel driving-related motor-cognitive functions from a panoply of test results, allowing for autonomous evaluation of driving aptitude in post-stroke individuals. This has the potential to reduce the number of screening tests required and the corresponding clinical workload, further improving personal and public safety and the quality of life of individuals with stroke.

Introduction: The peripheral arterial stiffness index has been proposed and validated as a noninvasive measure quantifying stimulus intensity based on amplitude changes induced by sympathetic innervation of vascular tone. However, its temporal response characteristics remain unclear, thus hindering continuous and accurate monitoring of the dynamic process of sympathetic activation. This paper presents a study aimed at modeling the transient response of the index across sensory stimuli to characterize the corresponding peripheral sympathetic activation.Methods: The index was measured using a continuous arterial pressure monitor and a pulse oximeter during experiments with local pain and local cooling stimuli designed to elicit different patterns of sympathetic activation. The corresponding response of the index was modeled to clarify its transient response characteristics across stimuli.Results: The constructed transfer function accurately depicted the transient response of the index to local pain and local cooling stimuli (Fit percentage: 78.4% ± 11.00% and 79.92% ± 8.79%). Differences in dead time (1.17 ± 0.67 and 0.99 ± 0.56 s, p = 0.082), peak time (2.89 ± 0.81 and 2.64 ± 0.68 s, p = 0.006), and rise time (1.81 ± 0.50 and 1.65 ± 0.48 s, p = 0.020) revealed different response patterns of the index across stimuli. The index also accurately characterized similar vasomotor velocities at different normalized peak amplitudes (0.19 ± 0.16 and 0.16 ± 0.19 a.u., p = 0.007).Discussion: Our findings flesh out the characterization of peripheral arterial stiffness index responses to different sensory stimuli and demonstrate its validity in characterizing peripheral sympathetic activation. This study valorizes a noninvasive method to characterize peripheral sympathetic activation, with the potential to use this index to continuously and accurately track sympathetic activators.

Abstract This study presents a novel approach for estimating vital capacity using cough sounds and proposes a neural network-based model that utilizes the reference vital capacity computed using the lambda-mu-sigma method, a conventional approach, and the cough peak flow computed based on the cough sound pressure level as inputs. Additionally, a simplified cough sound input model is developed, with the cough sound pressure level used directly as the input instead of the computed cough peak flow. A total of 56 samples of cough sounds and vital capacities were collected from 31 young and 25 elderly participants. Model performance was evaluated using squared errors, and statistical tests including the Friedman and Holm tests were conducted to compare the squared errors of the different models. The proposed model achieved a significantly smaller squared error (0.052 L2, p

Cardiopulmonary bypass (CPB) is an indispensable technique in cardiac surgery, providing the ability to temporarily replace cardiopulmonary function and create a bloodless surgical field. Traditionally, the operation of CPB systems has depended on the expertise and experience of skilled perfusionists. In particular, simultaneously controlling the arterial and venous occluders is difficult because the blood flow rate and reservoir level both change, and failure may put the patient’s life at risk. This study proposes an automatic control system with a two-degree-of-freedom model matching controller nested in an I-PD feedback controller to simultaneously regulate the blood flow rate and reservoir level. CPB operations were performed using glycerin and bovine blood as perfusate to simulate flow-up and flow-down phases. The results confirmed that the arterial blood flow rate followed the manually adjusted target venous blood flow rate, with an error of less than 5.32%, and the reservoir level was maintained, with an error of less than 3.44% from the target reservoir level. Then, we assessed the robustness of the control system against disturbances caused by venting/suction of blood. The resulting flow rate error was 5.95%, and the reservoir level error 2.02%. The accuracy of the proposed system is clinically satisfactory and within the allowable error range of 10% or less, meeting the standards set for perfusionists. Moreover, because of the system’s simple configuration, consisting of a camera and notebook PC, the system can easily be integrated with general CPB equipment. This practical design enables seamless adoption in clinical settings. With these advancements, the proposed system represents a significant step towards the automation of CPB.

Abstract The zebrafish is widely used as a model in biological studies. In particular, the heart rate and cortisol levels of zebrafish are commonly measured to elucidate the pharmacological effects of chemical substances. Meanwhile, although ventilation is also an important physiological index reflecting emotion-like states, few studies have evaluated the effects of chemicals on ventilation in adult zebrafish. In this study, we assessed whether it is possible to evaluate the pharmacological effects elicited by caffeine in adult zebrafish under free-swimming conditions. We measured the ventilation in adult zebrafish exposed to multiple concentrations of caffeine under restraint and free-swimming conditions and evaluated the pharmacological effects of caffeine using linear mixed model analysis. In addition, results of electrocardiogram analysis and swimming speeds were compared with those in previous reports to ensure that an appropriate dose of caffeine was administered. Under restraint conditions, caffeine significantly decreased heart rate and increased ventilation in a concentration-dependent manner. Under free-swimming conditions, the ventilation rate significantly increased with increasing caffeine concentration. These results indicate that the pharmacological effects elicited by chemicals on ventilation can be evaluated in free-swimming zebrafish.

Abstract Early intervention is now considered the core treatment strategy for autism spectrum disorders (ASD). Thus, it is of significant clinical importance to establish a screening tool for the early detection of ASD in infants. To achieve this goal, in a longitudinal design, we analyzed spontaneous bodily movements of 4-month-old infants from general population and assessed their ASD-like behaviors at 18 months of age. A total of 26 movement features were calculated from video-recorded bodily movements of infants at 4 months of age. Their risk of ASD was assessed at 18 months of age with the Modified Checklist for Autism in Toddlerhood, a widely used screening questionnaire. Infants at high risk for ASD at 18 months of age exhibited less rhythmic and weaker bodily movement patterns at 4 months of age than low-risk infants. When the observed bodily movement patterns were submitted to a machine learning-based analysis, linear and non-linear classifiers successfully predicted ASD-like behavior at 18 months of age based on the bodily movement patterns at 4 months of age, at the level acceptable for practical use. This study analyzed the relationship between spontaneous bodily movements at 4 months of age and the ASD risk at 18 months of age. Experimental results suggested the utility of the proposed method for the early screening of infants at risk for ASD. We revealed that the signs of ASD risk could be detected as early as 4 months after birth, by focusing on the infant’s spontaneous bodily movements.

Abstract Caenorhabditis elegans (C. elegans) can produce various motion patterns despite having only 69 motor neurons and 95 muscle cells. Previous studies successfully elucidate the connectome and role of the respective motor neuron classes related to movement. However, these models have not analyzed the distribution of the synaptic and gap connection weights. In this study, we examined whether a motor neuron and muscle network can generate oscillations for both forward and backward movement and analyzed the distribution of the trained synaptic and gap connection weights through a machine learning approach. This paper presents a connectome-based neural network model consisting of motor neurons of classes A, B, D, AS, and muscle, considering both synaptic and gap connections. A supervised learning method called backpropagation through time was adapted to train the connection parameters by feeding teacher data composed of the command neuron input and muscle cell activation. Simulation results confirmed that the motor neuron circuit could generate oscillations with different phase patterns corresponding to forward and backward movement, and could be switched at arbitrary times according to the binary inputs simulating the output of command neurons. Subsequently, we confirmed that the trained synaptic and gap connection weights followed a Boltzmann-type distribution. It should be noted that the proposed model can be trained to reproduce the activity patterns measured for an animal (HRB4 strain). Therefore, the supervised learning approach adopted in this study may allow further analysis of complex activity patterns associated with movements.

Abstract Muscle sympathetic nerve activity (MSNA) is known as an effective measure to evaluate peripheral sympathetic activity; however, it requires invasive measurement with the microneurography method. In contrast, peripheral arterial stiffness affected by MSNA is a measure that allows non-invasive evaluation of mechanical changes of arterial elasticity. This paper aims to clarify the features of peripheral arterial stiffness to determine whether it inherits MSNA features towards non-invasive evaluation of its activity. To this end, we propose a method to estimate peripheral arterial stiffness $$\beta$$ β at a high sampling rate. Power spectral analysis of the estimated $$\beta$$ β was then performed on data acquired from 15 patients ( $$23.7 \pm 9.0$$ 23.7 ± 9.0 years) who underwent endoscopic thoracic sympathectomy. We examined whether $$\beta$$ β exhibited the features of MSNA where its frequency components synchronise with heart and respiration rates and correlates with the low-frequency component of systolic blood pressure. Regression analysis revealed that the local peak frequency in the range of heartbeat frequency highly correlate with the heart rate ( $$R^{2}=0.85$$ R 2 = 0.85 , $$p=6.3\times 10^{-13}$$ p = 6.3 × 10 - 13 ) where the regression slope was approximately 1 and intercept was approximately 0. Frequency analysis then found spectral peaks of $$\beta$$ β approximately 0.2 Hz that correspond to the respiratory cycle. Finally, cross power spectral analysis showed a significant magnitude squared coherence between $$\beta$$ β and systolic blood pressure in the frequency band from 0.04 to 0.2 Hz. These results indicate that $$\beta$$ β inherits the features observed in MSNA that require invasive measurements, and thus $$\beta$$ β can be an effective non-invasive substitution for MSNA measure.

Abstract Brain activity associated with pain perception has been revealed by numerous PET and fMRI studies over the past few decades. These findings helped to establish the concept of the pain matrix, which is the distributed brain networks that demonstrate pain-specific cortical activities. We previously found that peripheral arterial stiffness $${\beta }_{\text{art}}$$ β art responds to pain intensity, which is estimated from electrocardiography, continuous sphygmomanometer, and photo-plethysmography. However, it remains unclear whether and to what extent $${\beta }_{\text{art}}$$ β art aligns with pain matrix brain activity. In this fMRI study, 22 participants received different intensities of pain stimuli. We identified brain regions in which the blood oxygen level-dependent signal covaried with $${\beta }_{\text{art}}$$ β art using parametric modulation analysis. Among the identified brain regions, the lateral and medial prefrontal cortex and ventral and dorsal anterior cingulate cortex were consistent with the pain matrix. We found moderate correlations between the average activities in these regions and $${\beta }_{\text{art}}$$ β art (r = 0.47, p

Abstract Fear, anxiety, and preference in fish are generally evaluated by video-based behavioural analyses. We previously proposed a system that can measure bioelectrical signals, called ventilatory signals, using a 126-electrode array placed at the bottom of an aquarium and achieved cameraless real-time analysis of motion and ventilation. In this paper, we propose a method to evaluate the emotional state of fish by combining the motion and ventilatory indices obtained with the proposed system. In the experiments, fear/anxiety and appetitive behaviour were induced using alarm pheromone and ethanol, respectively. We also found that the emotional state of the zebrafish can be expressed on the principal component (PC) space extracted from the defined indices. The three emotional states were discriminated using a model-based machine learning method by feeding the PCs. Based on discrimination performed every 5 s, the F-score between the three emotional states were as follows: 0.84 for the normal state, 0.76 for the fear/anxiety state, and 0.59 for the appetitive behaviour. These results indicate the effectiveness of combining physiological and motional indices to discriminate the emotional states of zebrafish.

Abstract The need for the estimation of the number of microbubbles (MBs) in cardiopulmonary bypass surgery has been recognized among surgeons to avoid postoperative neurological complications. MBs that exceed the diameter of human capillaries may cause endothelial disruption as well as microvascular obstructions that block posterior capillary blood flow. In this paper, we analyzed the relationship between the number of microbubbles generated and four circulation factors, i.e., intraoperative suction flow rate, venous reservoir level, continuous blood viscosity and perfusion flow rate in cardiopulmonary bypass, and proposed a neural-networked model to estimate the number of microbubbles with the factors. Model parameters were determined in a machine-learning manner using experimental data with bovine blood as the perfusate. The estimation accuracy of the model, assessed by tenfold cross-validation, demonstrated that the number of MBs can be estimated with a determinant coefficient R 2 = 0.9328 (p

This paper proposes a mathematical model for online prediction of the hematocrit- and temperature-based normal blood viscosity during cardiopulmonary bypass (CPB). Clinical trials were performed using a previously developed continuous blood viscosity monitoring system, and continuous pressure- and flow-based instantaneous viscosity (ηe) data were collected from 40 patients subjected to mild to moderate hypothermic CPB. The hematocrit and blood temperature data corresponding to ηe were also acquired. It was found that the blood viscosity-temperature curves for the different hematocrit levels can be well fitted using linear models, with the parameters of the linear model (slopes and intersects) also exhibiting linear relationships with the hematocrit. Based on these relationships, we were able to predict the hematocrit- and temperature-based normal viscosity (η0). To test the prediction accuracy, η0 was compared with ηe using the leave-one-out cross-validation procedure. Furthermore, η0 and the offline-measured viscosity (η), determined using a conventional viscometer, were compared for 20 patients subjected to mildly hypothermic CPB. η0 and ηe-two online blood viscosity monitoring methods based on different principles-showed good agreement (R2 = 0.74 and p 0 and η also showed good agreement (R2 = 0.69 and p

To date, a neuroscientific investigation of drivers' steering behavior has never been performed because the reaction forces generated by the mechanical characteristics of a steering wheel have been difficult to assess in a magnetic resonance imaging (MRI) environment. In this study, using our previously developed MRI-compatible unit for steering reaction force generation, we investigated changes in human brain activity induced by varying the viscoelastic characteristics associated with manipulating a car steering wheel. Participants performed a simulated driving task with three levels of stiffness and viscosity. An amplitude effect of reaction forces on the measured brain activity due to varying stiffness was found in the primary motor cortex (M1) associated with hand representation. Conversely, the changes in the brain activity induced by varying viscosity were found more dorsally in the premotor cortex and the M1 than in regions associated with hand representation. These results are the first to demonstrate that various viscoelastic characteristics activate different motor regions; more specifically, stiffness and viscosity of the steering wheel mainly affected the motor control of the distal and proximal muscles, respectively.

Cardiopulmonary bypass is a complex procedure that involves the maintenance of heart and lung functions using an external system during cardiac surgery. It is prone to significant human errors, which are mainly caused by inappropriate occluder operation that controls the perfusion balance by adjusting flow rates. Hence, there is a requirement for automatic occluder control; however, the relationship between occluder operation and flow rates remains unclear. The aim of this study is to use a steady-state model to evaluate the influence of occluder control on the flow and pressure of a cardiopulmonary bypass system. Perfusion experiments were performed using Newtonian (glycerin solution) and non-Newtonian (erythrocyte turbid solution) fluids to investigate the pressure-flow characteristics modulated by the occluder. We also visualized the fluid to verify the validity of the measurement data. Based on these experimental data, an exponential occlusion-pressure model is derived to express the relationships between the opening ratio of the occluder and flow rate. Estimation is then achieved by combining the occlusion-pressure model with the linear pressure-flow model. Results reveal that the combined model fitted the perfusion experiment data well for the venous and arterial line side (R2 = 0.946 and 0.985, respectively; p

Manipulation of light-matter interaction is critical in modern physics, especially in the strong coupling regime, where the generated half-light, half-matter bosonic quasiparticles as polaritons are important for fundamental quantum science and applications of optoelectronics and nonlinear optics. Two-dimensional transition metal dichalcogenides (TMDs) are ideal platforms to investigate the strong coupling because of their huge exciton binding energy and large absorption coefficients. Further studies on strong exciton-plasmon coupling by combining TMDs with metallic nanostructures have generated broad interests in recent years. However, because of the huge plasmon radiative damping, the observation of strong coupling is significantly limited at room temperature. Here, we demonstrate that a large Rabi splitting (~300 meV) can be achieved at ambient conditions in the strong coupling regime by embedding Ag-WS2 heterostructure in an optical microcavity. The generated quasiparticle with part-plasmon, part-exciton and part-light is analyzed with Hopfield coefficients that are calculated by using three-coupled oscillator model. The resulted plasmon-exciton polaritonic hybrid states can efficiently enlarge the obtained Rabi splitting, which paves the way for the practical applications of polaritonic devices based on ultrathin materials.