Real-time monitoring of cortical brain activity in response to acute pain using wide-area Ca2+ imaging

Previous human and rodent studies indicated that nociceptive stimuli activate many brain regions that is involved in the somatosensory and emotional sensation. Although these studies have identified several important brain regions involved in pain perception, it has been a challenge to observe neural activity directly and simultaneously in these multiple brain regions during pain perception. Using a transgenic mouse expressing G-CaMP7 in majority of astrocytes and a subpopulation of excitatory neurons, we recorded the brain activity in the mouse cerebral cortex during acute pain stimulation. Both of hind paw pinch and intraplantar administration of formalin caused strong transient increase of the fluorescence in several cortical regions, including primary somatosensory, motor and retrosplenial cortex. This increase of the fluorescence intensity was attenuated by the pretreatment with morphine. The present study provides important insight into the cortico-cortical network during pain perception.

Predictive value of magnetic resonance imaging diffusion parameters using artificial intelligence in low-and intermediate-risk prostate cancer patients treated with stereotactic ablative radiotherapy: A pilot study

INTRODUCTION

To investigate the predictive value of the pre-treatment diffusion parameters of diffusion-weighted magnetic resonance imaging (DW-MRI) using artificial intelligence (AI) for prostate-specific antigen (PSA) response in patients with low- and intermediate-risk prostate cancer (PCa) treated with stereotactic ablative radiotherapy (SABR).

METHODS

Retrospective evaluation was performed for 30 patients using pre-treatment multi-parametric MR image datasets between 2017 and 2021. MR-based mean- and minimum apparent diffusion coefficients (ADCmean, ADCmin) were calculated for the intraprostatic dominant lesion. Therapeutic response was assessed using PSA levels. Predictive performance was assessed by the receiver operating characteristic (ROC) analysis. Statistics performed with a significance level of p ≤ 0.05.

RESULTS

No biochemical relapse was detected after a median follow-up of twenty-three months (range: 3-50), with a median PSA of 0.01 ng/ml (range: 0.006-2.8) at the last examination. Significant differences were observed between the pre-treatment ADCmean, ADCmin parameters, and the group averages of patients with low and high 1-year-PSA measurements (p < 0.0001, p < 0.0001). In prediction, the random forest (RF) model outperformed the decision tree (DT) and support vector machine (SVM) models by yielding area under the curves (AUC), with 0.722, 0.685, and 0.5, respectively.

CONCLUSION

Our findings suggest that pre-treatment MR diffusion data may predict therapeutic response using the novel approach of machine learning in PCa patients treated with SABR.

IMPLICATIONS FOR PRACTICE

Clinicians shall measure and implement the evaluation of the suggested parameters (ADCmin, ADCmean) to provide the most accurate therapy for the patient.

Successful International EMBS Conference on Biomedical Engineering and Innovation Held in Hungary

The 1st IEEE Engineering in Medicine and Biology Society (EMBS) and the University of Pécs International Conference on Biomedical Engineering and Innovation (ICBEI) was held on 24-26 October 2022, in Pécs, Hungary. The conference opened with welcome talks by Prof. Attila Miseta, the rector of the University of Pécs (UP), Prof. Miklos Nyitrai, the dean of the UP, and Prof. Metin Akay, the president of IEEE EMBS, who delivered the first keynote talk at the conference. Then, we enjoyed three more exceptional keynote talks by Dr. Yasemin Akay, Dr. Gabor Forgacs, and Dr. Istvan Ulbert (Figure 1). With the participation of 230+ people, nine keynote lectures, and nine health care companies holding exhibitions, the conference was exceptional and well organized by Dr. Luca Toth, Dr. Adam Schiffer, and Dr. Peter Maroti, M.D., Ph.D., from the Centre for Biomedical Engineering and Innovation (Figure 2). The conference organizing team did a fantastic job. The attendance by several medical school students, the participation of health care companies (Figure 3), the hackathon competition, and several workshops were the highlights of the event. The first day of the conference concluded with a special wine tasting sponsored by the University of Pécs Wine Research Institute. Then, the conference organizing committee appreciation dinner hosted by Luca Tóth, Adam Schiffer, and Péter Maróti in the historical city of Pécs was indeed an exceptional social and cultural event (Figure 4).

Predicting Feeding Conditions of Premature InfantsThrough Non-Nutritive Sucking Skills Using a Sensitized Pacifier

Due to the lack of enough physical or suck central pattern generator (SCPG) development, premature infants require assistance in improving their sucking skills as one of the first coordinated muscular activities in infants. Hence, we need to quantitatively measure their sucking abilities for future studies on their sucking interventions. Here, we present a new device that can measure both intraoral pressure (IP) and expression pressure (EP) as ororhithmic behavior parameters of non-nutritive sucking skills in infants. Our device is low-cost, easy-to-use, and accurate, which makes it appropriate for extensive studies. To showcase one of the applications of our device, we collected weekly data from 137 premature infants from 29 week-old to 36 week-old. Around half of the infants in our study needed intensive care even after they were 36 week-old. We call them full attainment of oral feeding (FAOF) infants. We then used the Non-nutritive sucking (NNS) features of EP and IP signals of infants recorded by our device to predict FAOF infants' sucking conditions. We found that our pipeline can predict FAOF infants several weeks before discharge from the hospital. Thus, this application of our device presents a robust and inexpensive alternative to monitor oral feeding ability in premature infants.

Temozolomide in Combination With NF-κB Inhibitor Significantly Disrupts the Glioblastoma Multiforme Spheroid Formation

Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor, accounting for 50% of all cases. GBM patients have a five-year survival rate of merely 5.6% and a median overall survival of 14.6 months with the “Stupp” regimen, 20.9 months with tumor treatment fields (TTF, OptuneR) in patients who participated in clinical trials, and 11 months for all GBM patients prior to TTF use. Objective: Our group recently developed a brain cancer chip which generates tumor spheroids, and provides large-scale assessments on the response of tumor cells to various concentrations and combinations of drugs. This platform could optimize the use of tumor samples derived from GBM patients to provide valuable insight on the tumor growth and responses to drug therapies. To minimize any sample loss in vitro, we improved our brain cancer chip system by adding an additional laminar flow distribution layer, which reduces sample loss during cell seeding and prevents spheroids from escaping from the microwells. Methods: In this study, we cultured 3D spheroids from GBM cell lines and patient-derived GBM cells in vitro, and investigated the effect of the combination of Temozolomide and nuclear factor-κB inhibitor on tumor growth. Results: Our study revealed that these drugs have synergistic effects in inhibiting spheroid formation when used in combination. Conclusions: These results suggest that the brain cancer chip enables large-scale, inexpensive and sample-effective drug screening to 3D cancer tumors in vitro, and could be applied to related tissue engineering drug screening studies.

Drug Screening of Human GBM Spheroids in Brain Cancer Chip

Glioblastoma multiforme (GBM), an extremely invasive and high-grade (grade IV) glioma, is the most common and aggressive form of brain cancer. It has a poor prognosis, with a median overall survival of only 11 months in the general GBM population and 14.6 to 21 months in clinical trial participants with standard GBM therapies, including maximum safe craniotomy, adjuvant radiation, and chemotherapies. Therefore, new approaches for developing effective treatments, such as a tool for assessing tumor cell drug response before drug treatments are administered, are urgently needed to improve patient survival. To address this issue, we developed an improved brain cancer chip with a diffusion prevention mechanism that blocks drugs crossing from one channel to another. In the current study, we demonstrate that the chip has the ability to culture 3D spheroids from patient tumor specimen-derived GBM cells obtained from three GBM patients. Two clinical drugs used to treat GBM, temozolomide (TMZ) and bevacizumab (Avastin, BEV), were applied and a range of relative concentrations was generated by the microfluidic channels in the brain cancer chip. The results showed that TMZ works more effectively when used in combination with BEV compared to TMZ alone. We believe that this low-cost brain cancer chip could be further developed to generate optimal combination of chemotherapy drugs tailored to individual GBM patients.

Engineering a Brain Cancer Chip for High-throughput Drug Screening

Glioblastoma multiforme (GBM) is the most common and malignant of all human primary brain cancers, in which drug treatment is still one of the most effective treatments. However, existing drug discovery and development methods rely on the use of conventional two-dimensional (2D) cell cultures, which have been proven to be poor representatives of native physiology. Here, we developed a novel three-dimensional (3D) brain cancer chip composed of photo-polymerizable poly(ethylene) glycol diacrylate (PEGDA) hydrogel for drug screening. This chip can be produced after a few seconds of photolithography and requires no silicon wafer, replica molding, and plasma bonding like microfluidic devices made of poly(dimethylsiloxane) (PDMS). We then cultured glioblastoma cells (U87), which formed 3D brain cancer tissues on the chip, and used the GBM chip to perform combinatorial treatment of Pitavastatin and Irinotecan. The results indicate that this chip is capable of high-throughput GBM cancer spheroids formation, multiple-simultaneous drug administration, and a massive parallel testing of drug response. Our approach is easily reproducible, and this chip has the potential to be a powerful platform in cases such as high-throughput drug screening and prolonged drug release. The chip is also commercially promising for other clinical applications, including 3D cell culture and micro-scale tissue engineering.

Investigating the influence of PFC transection and nicotine on dynamics of AMPA and NMDA receptors of VTA dopaminergic neurons

Background

All drugs of abuse, including nicotine, activate the mesocorticolimbic system that plays critical roles in nicotine reward and reinforcement development and triggers glutamatergic synaptic plasticity on the dopamine (DA) neurons in the ventral tegmental area (VTA). The addictive behavior and firing pattern of the VTA DA neurons are thought to be controlled by the glutamatergic synaptic input from prefrontal cortex (PFC). Interrupted functional input from PFC to VTA was shown to decrease the effects of the drug on the addiction process. Nicotine treatment could enhance the AMPA/NMDA ratio in VTA DA neurons, which is thought as a common addiction mechanism. In this study, we investigate whether or not the lack of glutamate transmission from PFC to VTA could make any change in the effects of nicotine.

Methods

We used the traditional AMPA/NMDA peak ratio, AMPA/NMDA area ratio, and KL (Kullback-Leibler) divergence analysis method for the present study.

Results

Our results using AMPA/NMDA peak ratio showed insignificant difference between PFC intact and transected and treated with saline. However, using AMPA/NMDA area ratio and KL divergence method, we observed a significant difference when PFC is interrupted with saline treatment. One possible reason for the significant effect that the PFC transection has on the synaptic responses (as indicated by the AMPA/NMDA area ratio and KL divergence) may be the loss of glutamatergic inputs. The glutamatergic input is one of the most important factors that contribute to the peak ratio level.

Conclusions

Our results suggested that even within one hour after a single nicotine injection, the peak ratio of AMPA/NMDA on VTA DA neurons could be enhanced.

Prefrontal cortex deletion affects the dopaminergic neural firing complexity in nicotine-treated ventral tegmental area

Nicotine, an addictive substance in cigarette, triggers glutamatergic synaptic plasticity on ventral tegmental area (VTA) dopamine (DA) neurons. The functional coupling between prefrontal cortex (PFC) and VTA has been demonstrated, but little is known how PFC mediates nicotinic modulation in VTA DA neurons. In this study, we tested the hypothesis that systemic exposure to nicotine significantly increases the VTA DA neuron's complexity of firing. The complexity of the neural firing of VTA DA neurons was significantly increased in PFC intact subjects, as determined using the advanced nonlinear dynamic method based on the Lempel-Ziv estimator. To further understand the functional coupling between PFC and VTA, we used LZ complexity method to estimate the complexity of firing of PFC transected subjects. Interestingly, without the input from PFC, the change in complexity estimated from VTA for PFC transected subjects is not significant. The results suggest PFC plays an important role in mediating VTA activity and that the LZ complexity method is a useful tool for the characterization of the dynamical changes in VTA DA neurons firing activities.

Investigating the complexity of respiratory patterns during the laryngeal chemoreflex

Background

The laryngeal chemoreflex exists in infants as a primary sensory mechanism for defending the airway from the aspiration of liquids. Previous studies have hypothesized that prolonged apnea associated with this reflex may be life threatening and might be a cause of sudden infant death syndrome.

Methods

In this study we quantified the output of the respiratory neural network, the diaphragm EMG signal, during the laryngeal chemoreflex and eupnea in early postnatal (3–10 days) piglets. We tested the hypothesis that diaphragm EMG activity corresponding to reflex-related events involved in clearance (restorative) mechanisms such as cough and swallow exhibit lower complexity, suggesting that a synchronized homogeneous group of neurons in the central respiratory network are active during these events. Nonlinear dynamic analysis was performed using the approximate entropy to asses the complexity of respiratory patterns.

Results

Diaphragm EMG, genioglossal activity EMG, as well as other physiological signals (tracheal pressure, blood pressure and respiratory volume) were recorded from 5 unanesthetized chronically instrumented intact piglets. Approximate entropy values of the EMG during cough and swallow were found significantly (p < 0.05 and p < 0.01 respectively) lower than those of eupneic EMG.

Conclusion

Reduced complexity values of the respiratory neural network output corresponding to coughs and swallows suggest synchronous neural activity of a homogeneous group of neurons. The higher complexity values exhibited by eupneic respiratory activity are the result of a more random behaviour, which is the outcome of the integrated action of several groups of neurons involved in the respiratory neural network.

Complexity measures of the central respiratory networks during wakefulness and sleep

Since sleep is known to influence respiratory activity we studied whether the sleep state would affect the complexity value of the respiratory network output. Specifically, we tested the hypothesis that the complexity values of the diaphragm EMG (EMGdia) activity would be lower during REM compared to NREM. Furthermore, since REM is primarily generated by a homogeneous population of neurons in the medulla, the possibility that REM-related respiratory output would be less complex than that of the awake state was also considered. Additionally, in order to examine the influence of neuron vulnerabilities within the rostral ventral medulla (RVM) on the complexity of the respiratory network output, we inhibited respiratory neurons in the RVM by microdialysis of GABA(A) receptor agonist muscimol. Diaphragm EMG, nuchal EMG, EEG, EOG as well as other physiological signals (tracheal pressure, blood pressure and respiratory volume) were recorded from five unanesthetized chronically instrumented intact piglets (3-10 days old). Complexity of the diaphragm EMG (EMGdia) signal during wakefulness, NREM and REM was evaluated using the approximate entropy method (ApEn). ApEn values of the EMGdia during NREM and REM sleep were found significantly (p < 0.05 and p < 0.001, respectively) lower than those of awake EMGdia after muscimol inhibition. In the absence of muscimol, only the differences between REM and wakefulness ApEn values were found to be significantly different.