Computational Modeling of the Prefrontal-Cingulate Cortex to Investigate the Role of Coupling Relationships for Balancing Emotion and Cognition.

Within the prefrontal-cingulate cortex, abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions, contributing to the development of mental disorders such as depression. Despite this understanding, the neural circuit mechanisms underlying this phenomenon remain elusive. In this study, we present a biophysical computational model encompassing three crucial regions, including the dorsolateral prefrontal cortex, subgenual anterior cingulate cortex, and ventromedial prefrontal cortex. The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes. The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks. Furthermore, our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex, and network functionality was restored through intervention in the dorsolateral prefrontal cortex. This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.

Response of a neuronal network computational model to infrared neural stimulation.

Infrared neural stimulation (INS), as a novel form of neuromodulation, allows modulating the activity of nerve cells through thermally induced capacitive currents and thermal sensitivity ion channels. However, fundamental questions remain about the exact mechanism of INS and how the photothermal effect influences the neural response. Computational neural modeling can provide a powerful methodology for understanding the law of action of INS. We developed a temperature-dependent model of ion channels and membrane capacitance based on the photothermal effect to quantify the effect of INS on the direct response of individual neurons and neuronal networks. The neurons were connected through excitatory and inhibitory synapses and constituted a complex neuronal network model. Our results showed that a slight increase in temperature promoted the neuronal spikes and enhanced network activity, whereas the ultra-temperature inhibited neuronal activity. This biophysically based simulation illustrated the optical dose-dependent biphasic cell response with capacitive current as the core change condition. The computational model provided a new sight to elucidate mechanisms and inform parameter selection of INS.

Simultaneous Imaging of Bio- and Non-Conductive Targets by Combining Frequency and Time Difference Imaging Methods in Electrical Impedance Tomography.

As a promising medical imaging modality, electrical impedance tomography (EIT) can image the electrical properties within a region of interest using electrical measurements applied at electrodes on the region boundary. This paper proposes to combine frequency and time difference imaging methods in EIT to simultaneously image bio- and non-conductive targets, where the image fusion is accomplished by applying a wavelet-based technique. To enable image fusion, both time and frequency difference imaging methods are investigated regarding the reconstruction of bio- or non-conductive inclusions in the target region at varied excitation frequencies, indicating that none of those two methods can tackle with the scenarios where both bio- and non-conductive inclusions exist. This dilemma can be resolved by fusing the time difference (td) and appropriate frequency difference (fd) EIT images since they are complementary to each other. Through simulation and in vitro experiment, it is demonstrated that the proposed fusion method can reasonably reconstruct both the bio- and non-conductive inclusions within the lung models established to simulate the ventilation process, which is expected to be beneficial for the diagnosis of lung-tissue related diseases by EIT.

[Synthesis and biological evaluation of tetrahydrocoptisine quaternary ammonium compounds].

The goal of treatment of metabolic syndrome is the prevention of diabetes and cardiovascular events. A series of novel tetrahydrocoptisine quaternary ammonium compounds were prepared to evaluate their action of hypoglycemia and hypolipidemia for finding the therapeutic agents of metabolic syndrome. Starting from the coptisine hydrochloride (2), fifteen target compounds were synthesized by reduction and substitution of the 7-N position. All of the target compounds were characterized by 1H NMR and HR-MS. Their hypoglycemic activities were evaluated in HepG2 cell and hypolipidemic activities of compounds with better hypoglycemic activity were tested further in vivo. Results indicated that compounds 5, 7, 8 and 9 exhibited better hypoglycemic activities in vitro and compounds 5 and 8 exhibited good hypolipidemic activities in high-fat-diet (HFD) induced hyperlipidemia mice and (or) hamsters. However, the activity is not as good as simvastatin.