Synergistic effects of citicoline and silymarin nanomicelles in restraint stress-exposed mice.

This study evaluated the effects of citicoline and silymarin nanomicelles (SMnm) in repeated restraint stress (RRS). METHOD: Mice were exposed to RRS for four consecutive days, 2 hrs. daily. On day 5 of the study, SMnm (25 and 50 mg/kg, i.p.) and citicoline (25 and 75 mg/kg), and a combination of them (25 mg/kg, i.p.) were initiated. On day 18, anxiety-like behavior, behavioral despair, and exploratory behavior were evaluated. The prefrontal cortex (PFC) and the hippocampus were dissected measuring brain-derived neurotrophic factor (BDNF), cAMP response element-binding protein (CREB), and tumor necrosis factor-alpha (TNF-α) through Western Blot and ELISA, respectively. RESULTS: In RR-exposed mice, anxiety-like behavior in the elevated plus maze (EPM) was enhanced by reductions in open arm time (OAT%) P < 0.001, and open arm entry (OAE%) P < 0.001. In the forced swimming test (FST), the immobility increased P < 0.001 while the swimming and climbing reduced P < 0.001. In the open field test (OFT), general motor activity was raised P < 0.05. Further, body weights reduced P < 0.001, and tissue BDNF and pCREB expressions decreased P < 0.001 while TNF-α increased P < 0.001. Conversely, SMnm, citicoline and their combination could reduce anxiety-like behavior P < 0.001. The combination group reduced the depressive-like behaviors P < 0.001. Moreover, body weights were restored P < 0.001. Besides, BDNF and pCREB expressions increased while TNF-α reduced, P < 0.001. CONCLUSION: The combination synergistically improved emotion-like behaviors, alleviating the inflammation and upregulating the hippocampal BDNF-mediated CREB signaling pathway.

Machine learning approaches and non-linear processing of extracted components in frontal region to predict rTMS treatment response in major depressive disorder.

Predicting the therapeutic result of repetitive transcranial magnetic stimulation (rTMS) treatment could save time and costs as ineffective treatment can be avoided. To this end, we presented a machine-learning-based strategy for classifying patients with major depression disorder (MDD) into responders (R) and nonresponders (NR) to rTMS treatment. Resting state EEG data were recorded using 32 electrodes from 88 MDD patients before treatment. Then, patients underwent 7 weeks of rTMS, and 46 of them responded to treatment. By applying Independent Component Analysis (ICA) on EEG, we identified the relevant brain sources as possible indicators of neural activity in the dorsolateral prefrontal cortex (DLPFC). This was served through estimating the generators of activity in the sensor domain. Subsequently, we added physiological information and placed certain terms and conditions to offer a far more realistic estimation than the classic EEG. Ultimately, those components mapped in accordance with the region of the DLPFC in the sensor domain were chosen. Features extracted from the relevant ICs time series included permutation entropy (PE), fractal dimension (FD), Lempel-Ziv Complexity (LZC), power spectral density, correlation dimension (CD), features based on bispectrum, frontal and prefrontal cordance, and a combination of them. The most relevant features were selected by a Genetic Algorithm (GA). For classifying two groups of R and NR, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Multilayer Perceptron (MLP) were applied to predict rTMS treatment response. To evaluate the performance of classifiers, a 10-fold cross-validation method was employed. A statistical test was used to assess the capability of features in differentiating R and NR for further research. EEG characteristics that can predict rTMS treatment response were discovered. The strongest discriminative indicators were EEG beta power, the sum of bispectrum diagonal elements in delta and beta bands, and CD. The Combined feature vector classified R and NR with a high performance of 94.31% accuracy, 92.85% specificity, 95.65% sensitivity, and 92.85% precision using SVM. This result indicates that our proposed method with power and nonlinear and bispectral features from relevant ICs time-series can predict the treatment outcome of rTMS for MDD patients only by one session pretreatment EEG recording. The obtained results show that the proposed method outperforms previous methods.

Chromatin during plant regeneration: Opening towards root identity?

Plants show exceptional developmental plasticity and the ability to reprogram cell identities during regeneration. Although regeneration has been used in plant propagation for decades, we only recently gained detailed cellular and molecular insights into this process. Evidently, not all cell types have the same regeneration potential, and only a subset of regeneration-competent cells reach pluripotency. Pluripotent cells exhibit transcriptional similarity to root stem cells. In different plant regeneration systems, transcriptional reprogramming involves transient release of chromatin repression during pluripotency establishment and its restoration during organ or embryo differentiation. Incomplete resetting of the epigenome leads to somaclonal variation in regenerated plants. As single-cell technologies advance, we expect novel, exciting insights into epigenome dynamics during the establishment of pluripotency.

Production of Doubled Haploid Sugar Beet (Beta vulgaris L.) Plants Through Gynogenesis.

Haploid and doubled haploid plant production through unpollinated ovule culture, with diverse benefits and applications, is considered among the most effective and advantageous breeding method for sugar beet (Beta vulgaris L.). It is known that sugar beet is not responsive to androgenesis, which is widely used for most plant species. Sugar beet is a recalcitrant plant in vitro due to the very low spontaneous chromosome doubling and low gynogenesis rate. Thus, a steadily increasing gynogenesis efficiency has always been an important target for an efficient sugar beet breeding program. Given the scarcity of published papers focusing on gynogenesis in sugar beet, this chapter describes haploid and doubled haploid production through ovule culture of unfertilized flowers as a practical method.

Effects of cytokinins, gibberellic acid 3, and gibberellic acid 4/7 on in vitro growth, morphological traits, and content of steviol glycosides in Stevia rebaudiana.

Steviol glycosides (SGs) and gibberellic acids share a part of their biosynthesis pathways. Despite the widespread studies on the effect of gibberellic acid 3 (GA3), the effect of gibberellic acid 4 and 7 (GA4/7) on Stevia rebaudiana has never been studied. This study aimed at a comparative evaluation of different hormone effects, i.e., 1 mg L-1 GA4/7, 1 mg L-1 GA3, or 0.5 mg L-1 kinetin and 0.5 mg L-1 6-benzylaminopurine (BAP) (KB 0.5), on in vitro propagation, growth, morphological properties, and content of SGs in leaf samples of stevia. In comparison with the control group (hormone-free), the treatments of KB 0.5 or GA3 produced the highest biomasses and largest leaf areas. The three hormonal treatments produced a similar number of leaves, the ratio of fresh to dry weight, and leaf length. GA4/7-treated explants produced the highest ratio of leaf area to leaf length. The effect of GA4/7 on shoot elongation was greater than that of the control or even GA3. While the effect of GA3 on rebaudioside-A (Reb-A) production was similar to that of the control (16.2 and 18.04 mg g-1, respectively), GA4/7 resulted in a lower amount of it (13.31 mg g-1). Except for GA4/7, which induced more stevioside accumulation, the treatments' effects were comparable to that of the control. The ratio of stevioside to Reb-A was the highest for GA4/7 (2.62), followed by GA3 (1.93), and then the two others. Sum of Reb-A and stevioside content was not changed by the use of any of the treatments.