Fronto-medial electrode placement for electroconvulsive treatment of depression

Electroconvulsive therapy (ECT) is the most effective treatment for severe treatment-resistant depression but concern about cognitive side-effects, particularly memory loss, limits its use. Recent observational studies on large groups of patients who have received ECT report that cognitive side-effects were associated with electric field (EF) induced increases in hippocampal volume, whereas therapeutic efficacy was associated with EF induced increases in sagittal brain structures. The aim in the present study was to determine whether a novel fronto-medial (FM) ECT electrode placement would minimize electric fields in bilateral hippocampi (HIP) whilst maximizing electric fields in dorsal sagittal cortical regions. An anatomically detailed computational head model was used with finite element analysis, to calculate ECT-induced electric fields in specific brain regions identified by translational neuroimaging studies of treatment-resistant depressive illness, for a range of electrode placements. As hypothesized, compared to traditional bitemporal (BT) electrode placement, a specific FM electrode placement reduced bilateral hippocampal electric fields two-to-three-fold, whilst the electric fields in the dorsal anterior cingulate (dAC) were increased by approximately the same amount. We highlight the clinical relevance of this specific FM electrode placement for ECT, which may significantly reduce cognitive and non-cognitive side-effects and suggest a clinical trial is indicated

Comparison of Multi-Compartment Cable Models of Human Auditory Nerve Fibers

Background: Multi-compartment cable models of auditory nerve fibers have been developed to assist in the improvement of cochlear implants. With the advancement of computational technology and the results obtained from in vivo and in vitro experiments, these models have evolved to incorporate a considerable degree of morphological and physiological details. They have also been combined with three-dimensional volume conduction models of the cochlea to simulate neural responses to electrical stimulation. However, no specific rules have been provided on choosing the appropriate cable model, and most models adopted in recent studies were chosen without a specific reason or by inheritance. Methods: Three of the most cited biophysical multi-compartment cable models of the human auditory nerve, i.e., Rattay et al. (2001b), Briaire and Frijns (2005), and Smit et al. (2010), were implemented in this study. Several properties of single fibers were compared among the three models, including threshold, conduction velocity, action potential shape, latency, refractory properties, as well as stochastic and temporal behaviors. Experimental results regarding these properties were also included as a reference for comparison. Results: For monophasic single-pulse stimulation, the ratio of anodic vs. cathodic thresholds in all models was within the experimental range despite a much larger ratio in the model by Briaire and Frijns. For biphasic pulse-train stimulation, thresholds as a function of both pulse rate and pulse duration differed between the models, but none matched the experimental observations even coarsely. Similarly, for all other properties including the conduction velocity, action potential shape, and latency, the models presented different outcomes and not all of them fell within the range observed in experiments. Conclusions: While all three models presented similar values in certain single fiber properties to those obtained in experiments, none matched all experimental observations satisfactorily. In particular, the adaptation and temporal integration behaviors were completely missing in all models. Further extensions and analyses are required to explain and simulate realistic auditory nerve fiber responses to electrical stimulation

Two-stage Autoencoder Neural Network for 3D Speech Enhancement

3D speech enhancement has attracted much attention in recent years with the development of augmented reality technology. Traditional denoising convolutional autoencoders have limitations in extracting dynamic voice information. In this paper, we propose a two-stage autoencoder neural network for 3D speech enhancement. We incorporate a dual-path recurrent neural network block into the convolutional autoencoder to iteratively apply time-domain and frequency-domain modeling in an alternate fashion. And an attention mechanism for fusing the high-dimension features is proposed. We also introduce a loss function to simultaneously optimize the network in the time-frequency and time domains. Experimental results show that our system outperforms the state-of-the-art systems on the dataset of ICASSP L3DAS23 challenge.Comment: 5 pages,5 figure

14-3-3ε Boosts Bleomycin-induced DNA Damage Response by Inhibiting the Drug-resistant Activity of MVP

Major vault protein (MVP) is the predominant constituent of the vault particle, the largest known ribonuclear protein complex. Although emerging evidences have been establishing the links between MVP (vault) and multidrug resistance (MDR), little is known regarding exactly how the MDR activity of MVP is modulated during cellular response to drug-induced DNA damage (DDR). Bleomycin (BLM), an anti-cancer drug, induces DNA double-stranded breaks (DSBs) and consequently triggers the cellular DDR. Due to its physiological implications in hepatocellular carcinoma (HCC) and cell fate decision, 14-3-3ε was chosen as the pathway-specific bait protein to identify the critical target(s) responsible for HCC MDR. By using LC-MS/MS-based proteomic approach, MVP was first identified in the BLM-induced 14-3-3ε interactome formed in HCC cells. Biological characterization revealed that MVP possesses specific activity to promote the resistance to the BLM-induced DDR. On the other hand, 14-3-3ε enhances BLM-induced DDR by interacting with MVP. Mechanistic investigation further revealed that 14-3-3ε, in a phosphorylation-dependent manner, binds to the phosphorylated sites at both Thr52 and Ser864 of the monomer of MVP. Consequently, the phosphorylation-dependent binding between 14-3-3ε and MVP inhibits the drug-resistant activity of MVP for an enhanced DDR to BLM treatment. Our findings provide an insight into the mechanism underlying how the BLM-induced interaction between 14-3-3ε and MVP modulates MDR, implicating novel strategy to overcome the chemotherapeutic resistance through interfering specific protein-protein interactions

Micro-CT Synthesis and Inner Ear Super Resolution via Generative Adversarial Networks and Bayesian Inference

Existing medical image super-resolution methods rely on pairs of low- and high- resolution images to learn a mapping in a fully supervised manner. However, such image pairs are often not available in clinical practice. In this paper, we address super-resolution problem in a real-world scenario using unpaired data and synthesize linearly \textbf{eight times} higher resolved Micro-CT images of temporal bone structure, which is embedded in the inner ear. We explore cycle-consistency generative adversarial networks for super-resolution task and equip the translation approach with Bayesian inference. We further introduce \emph{Hu Moment distance} the evaluation metric to quantify the shape of the temporal bone. We evaluate our method on a public inner ear CT dataset and have seen both visual and quantitative improvement over state-of-the-art deep-learning-based methods. In addition, we perform a multi-rater visual evaluation experiment and find that trained experts consistently rate the proposed method the highest quality scores among all methods. Furthermore, we are able to quantify uncertainty in the unpaired translation task and the uncertainty map can provide structural information of the temporal bone.Comment: final version in ISBI 202

Exogenous Ca2+ priming can improve peanut photosynthetic carbon fixation and pod yield under early sowing scenarios in the field

Harnessing cold-resilient and calcium-enriched peanut production technology are crucial for high-yielding peanut cultivation in high-latitude areas. However, there is limited field data about how exogenous calcium (Ca2+) application would improve peanut growth resilience during exposure to chilling stress at early sowing (ES). To help address this problem, a two-year field study was conducted to assess the effects of exogenous foliar Ca2+ application on photosynthetic carbon fixation and pod yield in peanuts under different sowing scenarios. We measured plant growth indexes, leaf photosynthetic gas exchange, photosystems activities, and yield in peanuts. It was indicated that ES chilling stress at the peanut seedling stage led to the reduction of Pn, gs, Tr, Ls, WUE, respectively, and the excessive accumulation of non-structural carbohydrates in leaves, which eventually induced a chilling-dependent feedback inhibition of photosynthesis due mainly to weaken growth/sink demand. While exogenous Ca2+ foliar application improved the export of nonstructural carbohydrates, and photosynthetic capacity, meanwhile activated cyclic electron flow, thereby enhancing growth and biomass accumulation in peanut seedlings undergoing ES chilling stress. Furthermore, ES combined with exogenous Ca2+ application can significantly enhance plant chilling resistance and peanut yield ultimately in the field. In summary, the above results demonstrated that exogenous foliar Ca2+ application restored the ES-linked feedback inhibition of photosynthesis, enhancing the growth/sink demand and the yield of peanuts

Resilient and sustainable production of peanut (Arachis hypogaea) in phosphorus-limited environment by using exogenous gamma-aminobutyric acid to sustain photosynthesis

Globally, many low to medium yielding peanut fields have the potential for further yield improvement. Low phosphorus (P) limitation is one of the significant factors curtailing Arachis hypogaea productivity in many regions. In order to demonstrate the effects of gamma-aminobutyric acid (GABA) on peanuts growing under P deficiency, we used a pot-based experiment to examine the effects of exogenous GABA on alleviating P deficiency-induced physiological changes and growth inhibition in peanuts. The key physiological parameters examined were foliar gas exchange, photochemical efficiency, proton motive force, reactive oxygen species (ROS), and adenosine triphosphate (ATP) synthase activity of peanuts under cultivation with low P (LP, 0.5 mM P) and control conditions. During low P, the cyclic electron flow (CEF) maintained the high proton gradient (∆pH) induced by low ATP synthetic activity. Applying GABA during low P conditions stimulated CEF and reduced the concomitant ROS generation and thereby protecting the foliar photosystem II (PSII) from photoinhibition. Specifically, GABA enhanced the rate of electronic transmission of PSII (ETRII) by pausing the photoprotection mechanisms including non-photochemical quenching (NPQ) and ∆pH regulation. Thus, GABA was shown to be effective in restoring peanut growth when encountering P deficiency. Exogenous GABA alleviated two symptoms (increased root-shoot ratio and photoinhibition) of P-deficient peanuts. This is possibly the first report of using exogenous GABA to restore photosynthesis and growth under low P availability. Therefore, foliar applications of GABA could be a simple, safe and effective approach to overcome low yield imposed by limited P resources (low P in soils or P-fertilizers are unavailable) for sustainable peanut cultivation and especially in low to medium yielding fields

Computational models of electroconvulsive therapy and transcranial direct current stimulation for treatment of depression

Electroconvulsive therapy (ECT) and transcranial direct current stimulation (tDCS) are two important forms of transcranial electrical stimulation in clinical psychiatry. They have shown impressive therapeutic results in the treatment of major depression and other psychiatric disorders. The aim of this thesis was to develop novel computational models of ECT and tDCS to assist in the further understanding of these two brain-stimulation techniques, to explore possible refinements and improvements in treatment efficacy.Head models of three different subjects were reconstructed from corresponding computed tomography (CT) or magnetic resonance imaging (MRI) scans. One was a low-resolution model rendered from a set of CT scans, incorporating skull conductivity anisotropy. The other two were high-resolution models reconstructed from MRI scans, with one incorporating white matter conductivity anisotropy. In both high-resolution models, several brain cortical regions of interest were segmented and defined; these are known to be involved in therapeutic or adverse stimulation outcomes. In one set of simulations, these structural head models were taken to be passive volume conductors, to investigate the effect of various electrode montages on the distribution of current density or electric field within the head. Results showed that current distribution in the brain was highly dependent on the electrode placement on the scalp. For example, when simulating three different right unilateral (RUL) ECT montages, the non-conventional montages with an electrode on the forehead appeared to have superiority over conventional RUL, because stimulation strength was stronger in regions believed responsible for the treatment efficacy, such as the anterior cingulate gyrus, and was weaker in regions that have been speculated to exert adverse effects, such as the hippocampus.In addition, a continuum active model of neural excitation was also developed to simulate direct activation of the brain following an ECT stimulus. This model was integrated into the passive head model to investigate the influence of different electrode placements, as well as the time-dependent effects of ECT stimulus parameters on brain activation. For instance, when the stimulus pulse width was reduced, maximum current density was unchanged but the spatial extent of activation was reduced. Moreover, results showed that stimulus frequency influenced the stimulus efficiency, that is, of all the brain neurons that were able to be directly activated by a single pulse, 80%, 10% and 0% were capable of being activated by both of two consecutive pulses with frequencies of 60 Hz, 90 Hz and 120 Hz, respectively

The physiological functionality of PGR5/PGRL1-dependent cyclic electron transport in sustaining photosynthesis

The cyclic electron transport (CET), after the linear electron transport (LET), is another important electron transport pathway during the light reactions of photosynthesis. The proton gradient regulation 5 (PGR5)/PRG5-like photosynthetic phenotype 1 (PGRL1) and the NADH dehydrogenase-like complex pathways are linked to the CET. Recently, the regulation of CET around photosystem I (PSI) has been recognized as crucial for photosynthesis and plant growth. Here, we summarized the main biochemical processes of the PGR5/PGRL1-dependent CET pathway and its physiological significance in protecting the photosystem II and PSI, ATP/NADPH ratio maintenance, and regulating the transitions between LET and CET in order to optimize photosynthesis when encountering unfavorable conditions. A better understanding of the PGR5/PGRL1- mediated CET during photosynthesis might provide novel strategies for improving crop yield in a world facing more extreme weather events with multiple stresses affecting the plants