OsGSTU17, a Tau Class Glutathione S-Transferase Gene, Positively Regulates Drought Stress Tolerance in Oryza sativa.

As a great threat to the normal growth of rice, drought not only restricts the growth of rice, but also affects its yield. Glutathione S-transferases (GSTs) have antioxidant and detoxification functions. In rice, GSTs can not only effectively cope with biological stress, but also play a defense role against abiotic stress. In this study, we selected OsGSTU17, a member gene that was induced by drought, to explore the role of GSTs and analyze their physiological mechanisms that are involved in rice drought tolerance. With the CRISPR/Cas9 knockout system techniques, we obtained two independent mutant lines of osgstu17. After 14 days of drought stress treatment, and then re-supply of the water for 10 days, the survival rate of the osgstu17 mutant lines was significantly reduced compared to the wild-type (WT). Similarly, with the 10% (w/v) PEG6000 hydroponics experiment at the seedling stage, we also found that compared with the WT, the shoot and root biomass of osgstu17 mutant lines decreased significantly. In addition, both the content of the MDA and H2O2, which are toxic to plants, increased in the osgtu17 mutant lines. On the other hand, chlorophyll and proline decreased by about 20%. The activity of catalase and superoxide dismutase, which react with peroxides, also decreased by about 20%. Under drought conditions, compared with the WT, the expressions of the drought stress-related genes OsNAC10, OsDREB2A, OsAP37, OsP5CS1, OsRAB16C, OsPOX1, OsCATA, and OsCATB in the osgtu17 mutant lines were significantly decreased. Finally, we concluded that knocking out OsGSTU17 significantly reduced the drought tolerance of rice; OsGSTU17 could be used as a candidate gene for rice drought-tolerant cultivation. However, the molecular mechanism of OsGSTU17 involved in rice drought resistance needs to be further studied.

Independent Component and Graph Theory Analyses Reveal Normalized Brain Networks on Resting-State Functional MRI After Working Memory Training in People With HIV.

BACKGROUND: Cognitive training may partially reverse cognitive deficits in people with HIV (PWH). Previous functional MRI (fMRI) studies demonstrate that working memory training (WMT) alters brain activity during working memory tasks, but its effects on resting brain network organization remain unknown. PURPOSE: To test whether WMT affects PWH brain functional connectivity in resting-state fMRI (rsfMRI). STUDY TYPE: Prospective. POPULATION: A total of 53 PWH (ages 50.7 ± 1.5 years, two women) and 53 HIV-seronegative controls (SN, ages 49.5 ± 1.6 years, six women). FIELD STRENGTH/SEQUENCE: Axial single-shot gradient-echo echo-planar imaging at 3.0 T was performed at baseline (TL1), at 1-month (TL2), and at 6-months (TL3), after WMT. ASSESSMENT: All participants had rsfMRI and clinical assessments (including neuropsychological tests) at TL1 before randomization to Cogmed WMT (adaptive training, n = 58: 28 PWH, 30 SN; nonadaptive training, n = 48: 25 PWH, 23 SN), 25 sessions over 5-8 weeks. All assessments were repeated at TL2 and at TL3. The functional connectivity estimated by independent component analysis (ICA) or graph theory (GT) metrics (eigenvector centrality, etc.) for different link densities (LDs) were compared between PWH and SN groups at TL1 and TL2. STATISTICAL TESTS: Two-way analyses of variance (ANOVA) on GT metrics and two-sample t-tests on FC or GT metrics were performed. Cognitive (eg memory) measures were correlated with eigenvector centrality (eCent) using Pearson's correlations. The significance level was set at P < 0.05 after false discovery rate correction. RESULTS: The ventral default mode network (vDMN) eCent differed between PWH and SN groups at TL1 but not at TL2 (P = 0.28). In PWH, vDMN eCent changes significantly correlated with changes in the memory ability in PWH (r = -0.62 at LD = 50%) and vDMN eCent before training significantly correlated with memory performance changes (r = 0.53 at LD = 50%). DATA CONCLUSION: ICA and GT analyses showed that adaptive WMT normalized graph properties of the vDMN in PWH. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: 1.

A precise language network revealed by the independent component-based lesion mapping in post-stroke aphasia.

Brain lesion mapping studies have provided the strongest evidence regarding the neural basis of cognition. However, it remained a problem to identify symptom-specific brain networks accounting for observed clinical and neuroanatomical heterogeneity. Independent component analysis (ICA) is a statistical method that decomposes mixed signals into multiple independent components. We aimed to solve this issue by proposing an independent component-based lesion mapping (ICLM) method to identify the language network in patients with moderate to severe post-stroke aphasia. Lesions were first extracted from 49 patients with post-stroke aphasia as masks applied to fMRI data in a cohort of healthy participants to calculate the functional connectivity (FC) within the masks and non-mask brain voxels. ICA was further performed on a reformatted FC matrix to extract multiple independent networks. Specifically, we found that one of the lesion-related independent components (ICs) highly resembled classical language networks. Moreover, the damaged level within the language-related lesioned network is strongly associated with language deficits, including aphasia quotient, naming, and auditory comprehension scores. In comparison, none of the other two traditional lesion mapping methods found any regions responsible for language dysfunction. The language-related lesioned network extracted with the ICLM method showed high specificity in detecting aphasia symptoms compared with the performance of resting ICs and classical language networks. In total, we detected a precise language network in patients with aphasia and proved its efficiency in the relationship with language symptoms. In general, our ICLM could successfully identify multiple lesion-related networks from complicated brain diseases, and be used as an effective tool to study brain-behavior relationships and provide potential biomarkers of particular clinical behavioral deficits.

Prospective representations in rat orbitofrontal ensembles.

The orbitofrontal cortex (OFC) has been proposed to encode expected outcomes, which is thought to be important for outcome-directed behavior. However, such neural encoding can also often be explained by the recall of information about the recent past. To dissociate the retrospective and prospective aspects of encoding in the OFC, we designed a nonspatial, continuous, alternating odor-sequence task that mimicked a continuous T-maze. The task consisted of two alternating sequences of four odor-guided trials (2 sequences × 4 positions). In each trial, rats were asked to make a "go" or "no-go" action based on a fixed odor-reward contingency. Odors at both the first and last positions were distinct across the two sequences, such that they resembled unique paths in the past and future, respectively; odors at positions in between were the same and thus resembled a common path. We trained classifiers using neural activity to distinguish between either sequences or positions and asked whether the neural activity patterns in the common path were more like the ones in the past or the future. We found a proximal prospective code for sequence information as well as a distal perspective code for positional information, the latter of which was closely associated with rats' ability to predict future outcomes. This study demonstrates a behaviorally relevant predictive code in rat OFC. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Evolving schema representations in orbitofrontal ensembles during learning.

How do we learn about what to learn about? Specifically, how do the neural elements in our brain generalize what has been learned in one situation to recognize the common structure of-and speed learning in-other, similar situations? We know this happens because we become better at solving new problems-learning and deploying schemas1-5-through experience. However, we have little insight into this process. Here we show that using prior knowledge to facilitate learning is accompanied by the evolution of a neural schema in the orbitofrontal cortex. Single units were recorded from rats deploying a schema to learn a succession of odour-sequence problems. With learning, orbitofrontal cortex ensembles converged onto a low-dimensional neural code across both problems and subjects; this neural code represented the common structure of the problems and its evolution accelerated across their learning. These results demonstrate the formation and use of a schema in a prefrontal brain region to support a complex cognitive operation. Our results not only reveal a role for the orbitofrontal cortex in learning but also have implications for using ensemble analyses to tap into complex cognitive functions.

Serotonin neurons in the dorsal raphe nucleus encode reward signals.

The dorsal raphe nucleus (DRN) is involved in organizing reward-related behaviours; however, it remains unclear how genetically defined neurons in the DRN of a freely behaving animal respond to various natural rewards. Here we addressed this question using fibre photometry and single-unit recording from serotonin (5-HT) neurons and GABA neurons in the DRN of behaving mice. Rewards including sucrose, food, sex and social interaction rapidly activate 5-HT neurons, but aversive stimuli including quinine and footshock do not. Both expected and unexpected rewards activate 5-HT neurons. After mice learn to wait for sucrose delivery, most 5-HT neurons fire tonically during waiting and then phasically on reward acquisition. Finally, GABA neurons are activated by aversive stimuli but inhibited when mice seek rewards. Thus, DRN 5-HT neurons positively encode a wide range of reward signals during anticipatory and consummatory phases of reward responses. Moreover, GABA neurons play a complementary role in reward processing.

Prospective coding of dorsal raphe reward signals by the orbitofrontal cortex.

The orbitofrontal cortex (OFC) is important for the cognitive processes of learning and decision making. Previous recordings have revealed that OFC neurons encode predictions of reward outcomes. The OFC is interconnected with the dorsal raphe nucleus (DRN), which is a major serotonin (5-HT) center of the brain. Recent studies have provided increasing evidence that the DRN encodes reward signals. However, it remains unclear how the activity of DRN neurons affects the prospective reward coding of OFC neurons. By combining single-unit recordings from the OFC and optogenetic activation of the DRN in behaving mice, we found that DRN stimulation is sufficient to organize and modulate the anticipatory responses of OFC neurons. During pavlovian conditioning tasks for mice, odorant cues were associated with the delayed delivery of natural rewards of sucrose solution or DRN stimulation. After training, OFC neurons exhibited prospective responses to the sucrose solution. More importantly, the coupling of an odorant with delayed DRN stimulation resulted in tonic excitation or inhibition of OFC neurons during the delay period. The intensity of the prospective responses was affected by the frequency and duration of DRN stimulation. Additionally, DRN stimulation bidirectionally modulated the prospective responses to natural rewards. These experiments indicate that signals from the DRN are incorporated into the brain reward system to shape the cortical prospective coding of rewards.