Neisseria gonorrhoeae Infection in Women Increases With Rising Gonococcal Burdens in Partners: Chlamydia Coinfection in Women Increases Gonococcal Burden.

BACKGROUND: Likelihood of Neisseria gonorrhoeae infection in women exposed to male sex partners with increasing N. gonorrhoeae burdens and enhancement by Chlamydia trachomatis is not defined. METHODS: We identified men with urethritis and their regular female sex partners. Exposure to N. gonorrhoeae burdens in men was compared in N. gonorrhoeae-infected versus -uninfected partners. Association of N. gonorrhoeae infection in women with burdens in male partners was estimated using logistic regression. Association of C. trachomatis coinfection and N. gonorrhoeae burdens in women adjusted for burdens in male partners was estimated by linear regression. RESULTS: In total, 1816 men were enrolled; 202 had ≥2 partners, 91 who confirmed monogamy and were enrolled; 77% were married. Seventy were partners of N. gonorrhoeae-infected men; 58 (83%) were N. gonorrhoeae infected, 26 (45%) C. trachomatis coinfected. Infected women had partners with 9.3-fold higher N. gonorrhoeae burdens than partners of uninfected women (P = .0041). Association of N. gonorrhoeae infection in women with upper quartiles of N. gonorrhoeae burdens in partners increased (odds ratios ≥ 2.97)compared to the first quartile (P = .032). N. gonorrhoeae burdens in C. trachomatis-coinfected women were 2.82-fold higher than in C. trachomatis-uninfected women (P = .036). CONCLUSIONS: N. gonorrhoeae infections increased in women whose partners were infected with higher N. gonorrhoeae burdens. C. trachomatis coinfection was associated with increased N. gonorrhoeae burdens in women.

Echinochrome A Treatment Alleviates Fibrosis and Inflammation in Bleomycin-Induced Scleroderma.

Scleroderma is an autoimmune disease caused by the abnormal regulation of extracellular matrix synthesis and is activated by non-regulated inflammatory cells and cytokines. Echinochrome A (EchA), a natural pigment isolated from sea urchins, has been demonstrated to have antioxidant activities and beneficial effects in various disease models. The present study demonstrates for the first time that EchA treatment alleviates bleomycin-induced scleroderma by normalizing dermal thickness and suppressing collagen deposition in vivo. EchA treatment reduces the number of activated myofibroblasts expressing α-SMA, vimentin, and phosphorylated Smad3 in bleomycin-induced scleroderma. In addition, it decreased the number of macrophages, including M1 and M2 types in the affected skin, suggesting the induction of an anti-inflammatory effect. Furthermore, EchA treatment markedly attenuated serum levels of inflammatory cytokines, such as tumor necrosis factor-α and interferon-γ, in a murine scleroderma model. Taken together, these results suggest that EchA is highly useful for the treatment of scleroderma, exerting anti-fibrosis and anti-inflammatory effects.

Identification of asthma control factor in clinical notes using a hybrid deep learning model.

BACKGROUND: There are significant variabilities in guideline-concordant documentation in asthma care. However, assessing clinician's documentation is not feasible using only structured data but requires labor-intensive chart review of electronic health records (EHRs). A certain guideline element in asthma control factors, such as review inhaler techniques, requires context understanding to correctly capture from EHR free text. METHODS: The study data consist of two sets: (1) manual chart reviewed data-1039 clinical notes of 300 patients with asthma diagnosis, and (2) weakly labeled data (distant supervision)-27,363 clinical notes from 800 patients with asthma diagnosis. A context-aware language model, Bidirectional Encoder Representations from Transformers (BERT) was developed to identify inhaler techniques in EHR free text. Both original BERT and clinical BioBERT (cBERT) were applied with a cost-sensitivity to deal with imbalanced data. The distant supervision using weak labels by rules was also incorporated to augment the training set and alleviate a costly manual labeling process in the development of a deep learning algorithm. A hybrid approach using post-hoc rules was also explored to fix BERT model errors. The performance of BERT with/without distant supervision, hybrid, and rule-based models were compared in precision, recall, F-score, and accuracy. RESULTS: The BERT models on the original data performed similar to a rule-based model in F1-score (0.837, 0.845, and 0.838 for rules, BERT, and cBERT, respectively). The BERT models with distant supervision produced higher performance (0.853 and 0.880 for BERT and cBERT, respectively) than without distant supervision and a rule-based model. The hybrid models performed best in F1-score of 0.877 and 0.904 over the distant supervision on BERT and cBERT. CONCLUSIONS: The proposed BERT models with distant supervision demonstrated its capability to identify inhaler techniques in EHR free text, and outperformed both the rule-based model and BERT models trained on the original data. With a distant supervision approach, we may alleviate costly manual chart review to generate the large training data required in most deep learning-based models. A hybrid model was able to fix BERT model errors and further improve the performance.

Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique.

BACKGROUND: A subgroup of patients with asthma has been reported to have an increased risk for asthma-associated infectious and inflammatory multimorbidities (AIMs). To systematically investigate the association of asthma with AIMs using a large patient cohort, it is desired to leverage a broad range of electronic health record (EHR) data sources to automatically identify AIMs accurately and efficiently. METHODS: We established an expert consensus for an operational definition for each AIM from EHR through a modified Delphi technique. A series of questions about the operational definition of 19 AIMS (11 infectious diseases and 8 inflammatory diseases) was generated by a core team of experts who considered feasibility, balance between sensitivity and specificity, and generalizability. Eight internal and 5 external expert panelists were invited to individually complete a series of online questionnaires and provide judgement and feedback throughout three sequential internal rounds and two external rounds. Panelists' responses were collected, descriptive statistics tabulated, and results reported back to the entire group. Following each round the core team of experts made iterative edits to the operational definitions until a moderate (≥ 60%) or strong (≥ 80%) level of consensus among the panel was achieved. RESULTS: Response rates for each Delphi round were 100% in all 5 rounds with the achievement of the following consensus levels: (1) Internal panel consensus: 100% for 8 definitions, 88% for 10 definitions, and 75% for 1 definition, (2) External panel consensus: 100% for 12 definitions and 80% for 7 definitions. CONCLUSIONS: The final operational definitions of AIMs established through a modified Delphi technique can serve as a foundation for developing computational algorithms to automatically identify AIMs from EHRs to enable large scale research studies on patient's multimorbidities associated with asthma.

Theoretical Analysis for Using Pulsed Heating Power in Magnetic Hyperthermia Therapy of Breast Cancer.

In magnetic hyperthermia, magnetic nanoparticles (MNPs) are used to generate heat in an alternating magnetic field to destroy cancerous cells. This field can be continuous or pulsed. Although a large amount of research has been devoted to studying the efficiency and side effects of continuous fields, little attention has been paid to the use of pulsed fields. In this simulation study, Fourier's law and COMSOL software have been utilized to identify the heating power necessary for treating breast cancer under blood flow and metabolism to obtain the optimized condition among the pulsed powers for thermal ablation. The results showed that for small source diameters (not larger than 4 mm), pulsed powers with high duties were more effective than continuous power. Although by increasing the source domain the fraction of damage caused by continuous power reached the damage caused by the pulsed powers, it affected the healthy tissues more (at least two times greater) than the pulsed powers. Pulsed powers with high duty (0.8 and 0.9) showed the optimized condition and the results have been explained based on the Arrhenius equation. Utilizing the pulsed powers for breast cancer treatment can potentially be an efficient approach for treating breast tumors due to requiring lower heating power and minimizing side effects to the healthy tissues.

Theoretical Analysis for Wireless Magnetothermal Deep Brain Stimulation Using Commercial Nanoparticles.

A wireless magnetothermal stimulation (WMS) is suggested as a fast, tetherless, and implanted device-free stimulation method using low-radio frequency (100 kHz to 1 MHz) alternating magnetic fields (AMF). As magnetic nanoparticles (MNPs) can transduce alternating magnetic fields into heat, they are targeted to a region of the brain expressing the temperature-sensitive ion channel (TRPV1). The local temperature of the targeted area is increased up to 44 °C to open the TRPV1 channels and cause an influx of Ca2+ sensitive promoter, which can activate individual neurons inside the brain. The WMS has initially succeeded in showing the potential of thermomagnetics for the remote control of neural cell activity with MNPs that are internally targeted to the brain. In this paper, by using the steady-state temperature rise defined by Fourier's law, the bio-heat equation, and COMSOL Multiphysics software, we investigate most of the basic parameters such as the specific loss power (SLP) of MNPs, the injection volume of magnetic fluid, stimulation and cooling times, and cytotoxic effects at high temperatures (43-44 °C) to provide a realizable design guideline for WMS.

Does Nonmetropolitan Residence Impact Timely Chlamydia Treatment in Massachusetts?

A mean of 4.5 days until treatment was documented in a subset of reported laboratory-confirmed Massachusetts chlamydia cases selected for active case report form completion. Treatment delay was associated with longer test result turnaround time, and absence of symptoms or contact to sexually transmitted disease. Nonmetropolitan versus metropolitan residence did not appear to impact treatment time.

Source of Health Information and Unmet Healthcare Needs in Asian Americans.

BACKGROUND: Responding to the disparities in accessing and obtaining health information and healthcare among immigrant populations, the present study focused on Asian Americans. Using a sample that reflects Asian Americans' cultural and linguistic diversities, the goal was to explore the typologies of health information source and their predictability to unmet healthcare needs (i.e., the experience of not being able to get needed medical care). METHODS: Data were drawn from the 2015 Asian American Quality of Life Survey (N = 2,592), conducted using culturally and linguistically sensitive approaches. Latent class analysis on nine sources of health information across interpersonal networks (family members, close friends, acquaintances, and health professionals) and Internet-based communication technologies (mobile apps, email listservs, social networking sites, online communities, and health websites) identified six classes: 'resource-heavy,' 'human-oriented,' 'expertise-focused,' 'family-dominant,' 'resource-scarce,' and 'health professional-dominant.' RESULTS: Compared to the resource-heavy group, the odds of having an unmet healthcare need were 2.94 times greater in the family-dominant group and 4.13 times greater in the resource-scarce group. DISCUSSION: Findings provide implications for interventions with respect to subgroups to be prioritized and areas to be targeted in efforts to promote access and acquisition of health information and health services in Asian Americans.

Evaluating the effects of delivering integrated kinesthetic and tactile cues to individuals with unilateral hemiparetic stroke during overground walking.

BACKGROUND: Integration of kinesthetic and tactile cues for application to post-stroke gait rehabilitation is a novel concept which needs to be explored. The combined provision of haptic cues may result in collective improvement of gait parameters such as symmetry, balance and muscle activation patterns. Our proposed integrated cue system can offer a cost-effective and voluntary gait training experience for rehabilitation of subjects with unilateral hemiparetic stroke. METHODS: Ten post-stroke ambulatory subjects participated in a 10 m walking trial while utilizing the haptic cues (either alone or integrated application), at their preferred and increased gait speeds. In the system a haptic cane device (HCD) provided kinesthetic perception and a vibrotactile feedback device (VFD) provided tactile cue on the paretic leg for gait modification. Balance, gait symmetry and muscle activity were analyzed to identify the benefits of utilizing the proposed system. RESULTS: When using kinesthetic cues, either alone or integrated with a tactile cue, an increase in the percentage of non-paretic peak activity in the paretic muscles was observed at the preferred gait speed (vastus medialis obliquus: p <  0.001, partial eta squared (η2) = 0.954; semitendinosus p <  0.001, partial η2 = 0.793) and increased gait speeds (vastus medialis obliquus: p <  0.001, partial η2 = 0.881; semitendinosus p = 0.028, partial η2 = 0.399). While using HCD and VFD (individual and integrated applications), subjects could walk at their preferred and increased gait speeds without disrupting trunk balance in the mediolateral direction. The temporal stance symmetry ratio was improved when using tactile cues, either alone or integrated with a kinesthetic cue, at their preferred gait speed (p <  0.001, partial η2 = 0.702). CONCLUSIONS: When combining haptic cues, the subjects walked at their preferred gait speed with increased temporal stance symmetry and paretic muscle activity affecting their balance. Similar improvements were observed at higher gait speeds. The efficacy of the proposed system is influenced by gait speed. Improvements were observed at a 20% increased gait speed, whereas, a plateau effect was observed at a 40% increased gait speed. These results imply that integration of haptic cues may benefit post-stroke gait rehabilitation by inducing simultaneous improvements in gait symmetry and muscle activity.

Real-Time Two-Dimensional Magnetic Particle Imaging for Electromagnetic Navigation in Targeted Drug Delivery.

Magnetic nanoparticles (MNPs) are effective drug carriers. By using electromagnetic actuated systems, MNPs can be controlled noninvasively in a vascular network for targeted drug delivery (TDD). Although drugs can reach their target location through capturing schemes of MNPs by permanent magnets, drugs delivered to non-target regions can affect healthy tissues and cause undesirable side effects. Real-time monitoring of MNPs can improve the targeting efficiency of TDD systems. In this paper, a two-dimensional (2D) real-time monitoring scheme has been developed for an MNP guidance system. Resovist particles 45 to 65 nm in diameter (5 nm core) can be monitored in real-time (update rate = 2 Hz) in 2D. The proposed 2D monitoring system allows dynamic tracking of MNPs during TDD and renders magnetic particle imaging-based navigation more feasible.

A novel balance training system using multimodal biofeedback.

BACKGROUND: A biofeedback-based balance training system can be used to provide the compromised sensory information to subjects in order to retrain their sensorimotor function. In this study, the design and evaluation of the low-cost, intuitive biofeedback system developed at Gyeongsang National University is extended to provide multimodal biofeedback for balance training by utilization of visual and haptic modalities. METHODS: The system consists of a smartphone attached to the waist of the subject to provide information about tilt of the torso, a personal computer running a purpose built software to process the smartphone data and provide visual biofeedback to the subject by means of a dedicated monitor and a dedicated Phantom Omni(®) device for haptic biofeedback. For experimental verification of the system, eleven healthy young participants performed balance tasks assuming two distinct postures for 30 s each while acquiring torso tilt. The postures used were the one foot stance and the tandem Romberg stance. For both the postures, the subjects stood on a foam platform which provided a certain amount of ground instability. RESULTS: Post-experiment data analysis was performed using MATLAB(®) to analyze reduction in body sway. Analysis parameters based on the projection of trunk tilt information were calculated in order to ascertain the reduction in body sway and improvements in postural control. Two-way analysis of variance (ANOVA) showed no statistically significant interactions between postures and biofeedback. Post-hoc analysis revealed statistically significant reduction in body sway on provision of biofeedback. Subjects exhibited maximum body sway during no biofeedback trial, followed by either haptic or visual biofeedback and in most of the trials the multimodal biofeedback of visual and haptic together resulted in minimization of body sway, thus indicating that the multimodal biofeedback system worked well to provide significant (p < 0.05) assistance in postural control. CONCLUSIONS: A multimodal biofeedback system can offer more customized training methods and hence provide therapists with a comprehensive solution for a diverse array of patients. It is necessary to identify the long-term effects of this novel biofeedback system. In the future, the balance training schemes for individuals with upright balance issues will be studied.

In Silico Magnetic Nanocontainers Navigation in Blood Vessels: A Feedback Control Approach.

Magnetic nanoparticles (MNPs) are recently used in a drug delivery system to pass the blood brain barrier. However, because the magnetic force acting on particles is proportional to their volumes, as the size of particles is small, the large magnetic field is required to produce enough magnetic force for overcoming the hydrodynamic drag force as well as other forces in blood vessels. Other difficulties for controlling MNPs are the complicated behavior of hydrodynamic drag force and uncertain factors in their dynamics. Therefore, open-loop control methods cannot guarantee guiding every MNP to the correct location. Considering these challenges, this paper introduces a feedback control approach for magnetic nanoparticles (MNPs) in blood vessels. To the best of our knowledge, this is the first time feedback controller that is designed for MNPs without aggregation. Simulation studies in MATLAB and real-time verifications on a physical model in COMSOL-MATLAB interface are performed to prove the feasibility of the proposed approach. It is shown that the proposed control scheme can accurately and effectively navigate the MNP to the correct path with feasible hardware supports.

Effects of kinesthetic haptic feedback on standing stability of young healthy subjects and stroke patients.

BACKGROUND: Haptic control is a useful therapeutic option in rehabilitation featuring virtual reality interaction. As with visual and vibrotactile biofeedback, kinesthetic haptic feedback may assist in postural control, and can achieve balance control. Kinesthetic haptic feedback in terms of body sway can be delivered via a commercially available haptic device and can enhance the balance stability of both young healthy subjects and stroke patients. METHOD: Our system features a waist-attached smartphone, software running on a computer (PC), and a dedicated Phantom Omni® device. Young healthy participants performed balance tasks after assumption of each of four distinct postures for 30 s (one foot on the ground; the Tandem Romberg stance; one foot on foam; and the Tandem Romberg stance on foam) with eyes closed. Patient eyes were not closed and assumption of the Romberg stance (only) was tested during a balance task 25 s in duration. An Android application running continuously on the smartphone sent mediolateral (ML) and anteroposterior (AP) tilt angles to a PC, which generated kinesthetic haptic feedback via Phantom Omni®. A total of 16 subjects, 8 of whom were young healthy and 8 of whom had suffered stroke, participated in the study. RESULTS: Post-experiment data analysis was performed using MATLAB®. Mean Velocity Displacement (MVD), Planar Deviation (PD), Mediolateral Trajectory (MLT) and Anteroposterior Trajectory (APT) parameters were analyzed to measure reduction in body sway. Our kinesthetic haptic feedback system was effective to reduce postural sway in young healthy subjects regardless of posture and the condition of the substrate (the ground) and to improve MVD and PD in stroke patients who assumed the Romberg stance. Analysis of Variance (ANOVA) revealed that kinesthetic haptic feedback significantly reduced body sway in both categories of subjects. CONCLUSION: Kinesthetic haptic feedback can be implemented using a commercial haptic device and a smartphone. Intuitive balance cues were created using the handle of a haptic device, rendering the approach very simple yet efficient in practice. This novel form of biofeedback will be a useful rehabilitation tool improving the balance of stroke patients.

Treatment of Ischemic Stroke by Atorvastatin-Loaded PEGylated Liposome.

There is insufficient evidence on the effect of nanoparticles, particularly liposomes loaded with a statin, on acute ischemic stroke. We investigated the impact of atorvastatin-loaded PEG (polyethylene glycol) conjugated liposomes (LipoStatin) on the outcomes in rats with cerebral ischemia-reperfusion. PEGylated liposome loaded with atorvastatin was developed as a nanoparticle to specifically accumulate in an ischemic region and release the drug to ameliorate the harmful effects of the stroke. LipoStatin was administered to rats with transient middle cerebral artery occlusion through the tail vein immediately after reperfusion (LipoStatin group). LipoStatin efficiently accumulated at the cerebral ischemic injury site of the rat. The LipoStatin group showed a significantly reduced infarct volume (p < 0.01) in brain micro-MR imaging and improved neurological function recovery compared to the control group (p < 0.05). In addition, markedly improved brain metabolism using fluorine-18 fluorodeoxyglucose micro-PET/CT imaging was demonstrated in the LipoStatin group compared with the control group (p < 0.01). Mechanistically, as a result of evaluation through IL-1 beta, TNF-alpha, ICAM-1, and Iba-1 mRNA expression levels at 5 days after cerebral ischemia, LipoStatin showed significant anti-inflammatory effects. Protein expression of occludin, JAM-A, Caveolin-1, and eNOS by western blot at 3 days and fluorescent images at 7 days showed considerable recovery of blood-brain barrier breakdown and endothelial dysfunction. PEGylated LipoStatin can be more effectively delivered to the ischemic brain and may have significant neuroprotective effects. Thus, PEGylated LipoStatin can be further developed as a promising targeted therapy for ischemic stroke and other major vascular diseases.

Individual and collective manipulation of multifunctional bimodal droplets in three dimensions.

Spatiotemporally controllable droplet manipulation is vital across numerous applications, particularly in miniature droplet robots known for their exceptional deformability. Despite notable advancements, current droplet control methods are predominantly limited to two-dimensional (2D) deformation and motion of an individual droplet, with minimal exploration of 3D manipulation and collective droplet behaviors. Here, we introduce a bimodal actuation strategy, merging magnetic and optical fields, for remote and programmable 3D guidance of individual ferrofluidic droplets and droplet collectives. The magnetic field induces a magnetic dipole force, prompting the formation of droplet collectives. Simultaneously, the optical field triggers isothermal changes in interfacial tension through Marangoni flows, enhancing buoyancy and facilitating 3D movements of individual and collective droplets. Moreover, these droplets can function autonomously as soft robots, capable of transporting objects. Alternatively, when combined with a hydrogel shell, they assemble into jellyfish-like robots, driven by sunlight. These findings present an efficient strategy for droplet manipulation, broadening the capabilities of droplet-based robotics.

Towards human-scale magnetic particle imaging: development of the first system with superconductor-based selection coils.

Magnetic Particle Imaging (MPI) is an emerging tomographic modality that allows for precise three-dimensional (3D) mapping of magnetic nanoparticles (MNPs) concentration and distribution. Although significant progress has been made towards improving MPI since its introduction, scaling it up for human applications has proven challenging. High-quality images have been obtained in animal-scale MPI scanners with gradients up to 7 T/m/µ0, however, for MPI systems with bore diameters around 200 mm the gradients generated by electromagnets drop significantly to below 0.5 T/m/µ0. Given the current technological limitations in image reconstruction and the properties of available MNPs, these low gradients inherently impose limitations on improving MPI resolution for higher precision medical imaging. Utilizing superconductors stands out as a promising approach for developing a human-scale MPI system. In this study, we introduce, for the first time, a human-scale amplitude-modulated (AM) MPI system with superconductor-based selection coils. The system achieves an unprecedented magnetic field gradient of up to 2.5 T/m/µ0 within a 200 mm bore diameter, enabling large fields of view of 100 × 130 × 98 mm3 at 2.5 T/m/µ0 for 3D imaging. While obtained spatial resolution is in the order of previous animal-scale AM MPIs, incorporating superconductors for achieving such high gradients in a 200 mm bore diameter marks a major step toward clinical MPI.

Magnetic particle image scanner based on asymmetric core-filled electromagnetic actuator.

Monitoring the distribution of magnetic nanoparticles (MNPs) in the vascular system is an important task for the advancement of precision therapeutics and drug delivery. Despite active targeting using active motilities, it is required to visualize the position and concentration of carriers that reach the target, to promote the development of this technology. In this work, a feasibility study is presented on a tomographic scanner that allows monitoring of the injected carriers quantitatively in a relatively short interval. The device is based on a small-animal-scale asymmetric magnetic platform integrated with magnetic particle imaging technology. An optimized isotropic field-free region (FFR) generation method using a magnetic manipulation system (MMS) is derived and numerically investigated. The in-vitro and in-vivo tracking performances are demonstrated with a high position accuracy of approximately 1 mm. A newly proposed tracking method was developed, specialized in vascular system, with quick scanning time (about 1s). In this paper, the primary function of the proposed system is to track magnetic particles using a magnetic manipulation system. Through this, proposed method enables the conventional magnetic actuation systems to upgrade the functionalities of both manipulation and localization of magnetic objects.

A prediction model for magnetic particle imaging-based magnetic hyperthermia applied to a brain tumor model.

BACKGROUND AND OBJECTIVE: Brain tumor is a global health concern at the moment. Thus far, the only treatments available are radiotherapy and chemotherapy, which have several drawbacks such as low survival rates and low treatment efficacy due to obstruction of the blood-brain barrier. Magnetic hyperthermia (MH) using magnetic nanoparticles (MNPs) is a promising non-invasive approach that has the potential for tumor treatment in deep tissues. Due to the limitations of the current drug-targeting systems, only a small proportion of the injected MNPs can be delivered to the desired area and the rest are distributed throughout the body. Thus, the application of conventional MH can lead to damage to healthy tissues. METHODS: Magnetic particle imaging (MPI)-guided treatment platform for MH is an emerging approach that can be used for spatial localization of MH to arbitrarily selected regions by using the MPI magnetic field gradient. Although the feasibility of this method has been demonstrated experimentally, a multidimensional prediction model, which is of crucial importance for treatment planning, has not yet been developed. Hence, in this study, the time dependent magnetization equation derived by Martsenyuk, Raikher, and Shliomis (which is a macroscopic equation of motion derived from the Fokker-Planck equation for particles with Brownian relaxation mechanism) and the bio-heat equations have been used to develop and investigate a three-dimensional model that predicts specific loss power (SLP), its spatio-thermal resolution (temperature distribution), and the fraction of damage in brain tumors. RESULTS: Based on the simulation results, the spatio-thermal resolution in focused heating depends, in a complex manner, on several parameters ranging from MNPs properties to magnetic fields characteristics, and coils configuration. However, to achieve a high performance in focused heating, the direction and the relative amplitude of the AC magnetic heating field with respect to the magnetic field gradient are among the most important parameters that need to be optimized. The temperature distribution and fraction of the damage in a simple brain model bearing a tumor were also obtained. CONCLUSIONS: The complexity in the relationship between the MNPs properties and fields parameter imposes a trade-off between the heating efficiency of MNPs and the accuracy (resolution) of the focused heating. Therefore, the system configuration and field parameters should be chosen carefully for each specific treatment scenario. In future, the results of the model are expected to lead to the development of an MPI-guided MH treatment platform for brain tumor therapy. However, for more accurate quantitative results in such a platform, a magnetization dynamics model that takes into account coupled Néel-Brownian relaxation mechanism in the MNPs should be developed.

Magnetothermal-based non-invasive focused magnetic stimulation for functional recovery in chronic stroke treatment.

Magnetic heat-based brain stimulation of specific lesions could promote the restoration of impaired motor function caused by chronic stroke. We delivered localized stimulation by nanoparticle-mediated heat generation within the targeted brain area via focused magnetic stimulation. The middle cerebral artery occlusion model was prepared, and functional recovery in the chronic-phase stroke rat model was demonstrated by the therapeutic application of focused magnetic stimulation. We observed a transient increase in blood-brain barrier permeability at the target site of < 4 mm and metabolic brain activation at the target lesion. After focused magnetic stimulation, the rotarod score increased by 390 ± 28% (p < 0.05) compared to the control group. Standardized uptake value in the focused magnetic stimulation group increased by 2063 ± 748% (p < 0.01) compared to the control group. Moreover, an increase by 24 ± 5% (p < 0.05) was observed in the sham group as well. Our results show that non-invasive focused magnetic stimulation can safely modulate BBB permeability and enhance neural activation for chronic-phase stroke treatment in the targeted deep brain area.

A Machine Learning-Based Initial Difficulty Level Adjustment Method for Balance Exercise on a Trunk Rehabilitation Robot.

Trunk rehabilitation exercises such as those for remediating core stability can help improve the seated balance of patients with weakness or loss of proprioception caused by diseases such as stroke, and aid the recovery of other functions such as gait. However, there has not yet been any reported method for automatically determining the parameters that define exercise difficulty on a trunk rehabilitation robot (TRR) based on data such as the patient's demographic information, balancing ability, and training sequence, etc. We have proposed a machine learning (ML)-based difficulty adjustment method to determine an appropriate virtual damping gain (Dvirtual) of the controller for the TRR's unstable training mode. Training data for the proposed system is obtained from 37 healthy young adults, and the trained ML model thus obtained is tested through experiments with a separate population of 25 healthy young adults. The leave-one-out cross validation results (37 subjects) from the training group for validation of the designed ML model showed 80.90% average accuracy (R2 score) for using the given information to predict the desired difficulty levels, which are represented by the level of balance performance quantified as Mean Velocity Displacement (MVD) of the center of pressure. Statistical analysis (Repeated measures analysis of variance) of subject performance also showed that ground truth difficulty levels from the training data and predicted difficulty levels did not differ significantly under any of the three exercise modes used in this study (Hard, Medium, and Easy), and the standard deviations were reduced by 16.39, 41.39, and 25.68%, respectively. Moreover, the Planar Deviation (PD) of the center of pressure, which was not the target parameter here, also showed results similar to the MVD, which indicates that the predicted Dvirtual affected the difficulty level of balance performance. Therefore, the proposed ML model-based difficulty adjustment method has potential for use with people who have varied balancing abilities.