Aberrant brain dynamics in major depressive disorder during working memory task.

Working memory (WM) is a distributed and dynamic process, and WM deficits are recognized as one of the top-ranked endophenotype candidates for major depressive disorders (MDD). However, there is a lack of knowledge of brain temporal-spatial profile of WM deficits in MDD. We used the dynamical degree centrality (dDC) to investigate the whole-brain temporal-spatial profile in 40 MDD and 40 controls during an n-back task with 2 conditions (i.e., '0back' and '2back'). We explored the dDC temporal variability and clustered meta-stable states in 2 groups during different WM conditions. Pearson's correlation analysis was used to evaluate the relationship between the altered dynamics with clinical symptoms and WM performance. Compared with controls, under '2back vs. 0back' contrast, patients showed an elevated dDC variability in wide range of brain regions, including the middle frontal gyrus, orbital part of inferior frontal gyrus (IFGorb), hippocampus, and middle temporal gyrus. Furthermore, the increased dDC variability in the hippocampus and IFGorb correlated with worse WM performance. However, there were no significant group-related differences in the meta-stable states were observed. This study demonstrated the increased WM-related instability (i.e., the elevated dDC variability) was represented in MDD, and enhancing stability may help patients achieve better WM performance.

The centrality of working memory networks in differentiating bipolar type I depression from unipolar depression: A task-fMRI study.

OBJECTIVES: Up to 70%-80% of patients with bipolar disorder are misdiagnosed as having major depressive disorder (MDD), leading to both delayed intervention and worsening disability. Differences in the cognitive neurophysiology may serve to distinguish between the depressive phase of type 1 bipolar disorder (BDD-I) from MDD, though this remains to be demonstrated. To this end, we investigate the discriminatory signal in the topological organization of the functional connectome during a working memory (WM) task in BDD-I and MDD, as a candidate identification approach. METHODS: We calculated and compared the degree centrality (DC) at the whole-brain voxel-wise level in 31 patients with BDD-I, 35 patients with MDD, and 80 healthy controls (HCs) during an n-back task. We further extracted the distinct DC patterns in the two patient groups under different WM loads and used machine learning approaches to determine the distinguishing ability of the DC map. RESULTS: Patients with BDD-I had lower accuracy and longer reaction time (RT) than HCs at high WM loads. BDD-I is characterized by decreased DC in the default mode network (DMN) and the sensorimotor network (SMN) when facing high WM load. In contrast, MDD is characterized by increased DC in the DMN during high WM load. Higher WM load resulted in better classification performance, with the distinct aberrant DC maps under 2-back load discriminating the two disorders with 90.91% accuracy. CONCLUSIONS: The distributed brain connectivity during high WM load provides novel insights into the neurophysiological mechanisms underlying cognitive impairment of depression. This could potentially distinguish BDD-I from MDD if replicated in future large-scale evaluations of first-episode depression with longitudinal confirmation of diagnostic transition.

Single-molecule multiplexed profiling of protein-DNA complexes using magnetic tweezers.

Epigenetics, such as the dynamic interplay between DNA methylation and demethylation, play diverse roles in critical cellular events. Enzymatic activity at CpG sites, where cytosines are methylated or demethylated, is known to be influenced by the density of CpGs, methylation states, and the flanking sequences of a CpG site. However, how the relevant enzymes are recruited to and recognize their target DNA is less clear. Moreover, although DNA-binding epigenetic enzymes are ideal targets for therapeutic intervention, these targets have been rarely exploited. Single-molecule techniques offer excellent capabilities to probe site-specific protein-DNA interactions and unravel the dynamics. Here, we develop a single-molecule approach that allows multiplexed profiling of protein-DNA complexes using magnetic tweezers. When a DNA hairpin with multiple binding sites is unzipping, strand separation pauses at the positions bound by a protein. We can thus measure site-specific binding probabilities and dissociation time directly. Taking the TET1 CXXC domain as an example, we show that TET1 CXXC binds multiple CpG motifs with various flanking nucleotides or different methylation patterns in an AT-rich DNA. We are able to establish for the first time, at nanometer resolution, that TET1 CXXC prefers G/C flanked CpG motif over C/G, A/T, or T/A flanked ones. CpG methylation strengthens TET1 CXXC recruitment but has little effect on dissociation time. Finally, we demonstrate that TET1 CXXC can distinguish five CpG clusters in a CpG island with crowded binding motifs. We anticipate that the feasibility of single-molecule multiplexed profiling assays will contribute to the understanding of protein-DNA interactions.

A Unified Global Reference Frame of Vertical Crustal Movements by Satellite Laser Ranging.

Crustal movement is one of the main factors influencing the change of the Earth system, especially in its vertical direction, which affects people's daily life through the frequent occurrence of earthquakes, geological disasters, and so on. In order to get a better study and application of the vertical crustal movement,as well as its changes, the foundation and prerequisite areto devise and establish its reference frame; especially, a unified global reference frame is required. Since SLR (satellite laser ranging) is one of the most accurate space techniques for monitoring geocentric motion and can directly measure the ground station's geocentric coordinates and velocities relative to the centre of the Earth's mass, we proposed to take the vertical velocity of the SLR technique in the ITRF2008 framework as the reference frame of vertical crustal motion, which we defined as the SLR vertical reference frame (SVRF). The systematic bias between other velocity fields and the SVRF was resolved by using the GPS (Global Positioning System) and VLBI (very long baseline interferometry) velocity observations, and the unity of other velocity fields and SVRF was realized,as well. The results show that it is feasible and suitable to take the SVRF as a reference frame, which has both geophysical meanings and geodetic observations, so we recommend taking the SLR vertical velocity under ITRF2008 as the global reference frame of vertical crustal movement.

Evaluation methods of BDS-3 ground-segment defensive capability oriented to satellite navigation countermeasures.

Owing to intentional interference and destructions during satellite navigation countermeasures, the security application of global navigation satellite systems (GNSS) faces immense challenges. To ensure the safe application of the GNSS in complex electromagnetic environment, the system-level defensive capability need be assessed, which can make for maintaining GNSS normal service during countering and further realizing the optimal decision. Therefore, this study used the ground control segment in the GNSS as the evaluation object, the bottom indices related to the criterion layers including service performance and station function as the key evaluation indices, and the technical requirement of each index under a secure situation as the standard, to propose the evaluation system including index system and evaluation methods for the ground-segment defensive capability. As BeiDou navigation satellite system III (BDS-3) is a global navigation satellite system independently built and operated by China, it was taken as a case for method verification. Then, BDS-3 two-way observation data between the satellite and the ground and between stations, which was collected from Beijing flight Control Center, from March 5 to 12 (2022) were selected during tests, and the results were compared with the existing standards contained in BDS open service performance standard to evaluate the system-level defensive capability. Evaluation Results of positioning accuracy and error correction ability for the BDS-3's ground stations determined through seven damage experiments with different interference strength show that: Corresponding horizontal and vertical positioning accuracy of stations under test did not exceed 1 m in the statistical period and their convergence time did not exceed the limit (30 min); thus, the ground segment of the BDS-3 has a good defensive capability. Compared to comprehensive evaluation results of the BDS-3, based on the theoretical threshold (the ground-segment threshold ≤48.40 % and the space-segment threshold ≤51.60 %), we know that its ground-segment defense (14.06 %) was worse than GPS ground-segment defense (14.43 %), whereas the ground-segment defense of the BDS/GPS integrated system (15.29 %) was best and its capability evaluation grade was strong. They indicate system's future improvements should focus more on enhancing the development scale and service efficiency of the BDS-3's ground stations in the Western Hemisphere, and reasonably promote system compatibility and interoperability while considering facility cost and operating efficiency.

The neural compensation phenomenon in schizophrenia with mild attention deficits during working memory task.

BACKGROUND: Working memory (WM) and attention are essential cognitive processes, and their interplay is critical for efficient information processing. Schizophrenia often exhibits deficits in both WM and attention, contributing to function impairments. This study aims to investigate the neural mechanisms underlying the relationship between WM impairments and attention deficits in schizophrenia. METHODS: We assessed the functional-MRI scans of the 184 schizophrenias with different attention deficits (mild=133; severe=51) and 146 controls during an N-back WM task. We explored their whole-brain functional connectome profile by adopting the voxel-wise degree centrality (DC). Linear analysis was conducted to explore the associations among attention deficit severity, altered DC, and WM performance in patients. RESULTS: We observed that all patients showed decreased DC in the pre-supplementary area (pre-SMA), and posterior cerebellum compared to the controls, and schizophrenia patients with mild attention deficits showed decreased DC in the supramarginal gyrus, insula, and precuneus compared with the other 2 groups. DC values of the detected brain regions displayed U-shaped or inverted U-shaped curves, rather than a linear pattern, in response to increasing attention deficits. The linear analysis indicated that altered DC of the pre-SMA can modulate the relationship between attention deficits and WM performance. CONCLUSION: The U-shaped or inverted U-shaped pattern in response to increasing attention deficits may reflect a compensation mechanism in schizophrenia with mild attention deficits. This notion is also supported by the linear analysis that schizophrenia patients with mild attention deficits can improve their WM performance by increasing the DC value of the pre-SMA.

The anatomical networks based on probabilistic structurally connectivity in bipolar disorder across mania, depression, and euthymic states.

BACKGROUNDS: There have pieces of evidence of the distinct aberrant functional network topology profile in bipolar disorder (BD) across mania, depression, and euthymic episodes. However, the underlying anatomical network topology pattern in BD across different episodes is unclear. METHODS: We calculated the whole-brain probabilistic structurally connectivity across 143 subjects (72 with BD [34 depression; 13 mania; 25 euthymic] and 53 healthy controls), and used graph theory to examine the trait- and state-related topology alterations of the structural connectome in BD. The correlation analysis was further conducted to explore the relationship between detected network measures and clinical symptoms. RESULTS: There no omnibus alteration of any global network metrics were observed across all diagnostic groups. In the regional network metrics level, bipolar depression showed increased clustering coefficient in the right lingual gyrus compared with all other groups, and the increased clustering coefficient in the right lingual gyrus positively correlated with depression, anxiety, and illness burden symptoms but negatively correlated with mania symptoms; manic and euthymic patients showed decreased clustering coefficient in the left inferior occipital gyrus compared with HCs. LIMITATIONS: The moderate sample size of all patient groups (especially for subjects with mania) might have contributed to the negative findings of the trait feature in this study. CONCLUSIONS: We demonstrated the altered regional connectivity pattern in the occipital lobe of the bipolar depression and mania episode, especially the lingual gyrus. The association of the clustering coefficient in the lingual gyrus with clinical symptoms helps monitor the state of BD.

Hypoactive Visual Cortex, Prefrontal Cortex and Insula during Self-Face Recognition in Adults with First-Episode Major Depressive Disorder.

Self-face recognition is a vital aspect of self-referential processing, which is closely related to affective states. However, neuroimaging research on self-face recognition in adults with major depressive disorder is lacking. This study aims to investigate the alteration of brain activation during self-face recognition in adults with first-episode major depressive disorder (FEMDD) via functional magnetic resonance imaging (fMRI); FEMDD (n = 59) and healthy controls (HC, n = 36) who performed a self-face-recognition task during the fMRI scan. The differences in brain activation signal values between the two groups were analyzed, and Pearson correlation analysis was used to evaluate the relationship between the brain activation of significant group differences and the severity of depressive symptoms and negative self-evaluation; FEMDD showed significantly decreased brain activation in the bilateral occipital cortex, bilateral fusiform gyrus, right inferior frontal gyrus, and right insula during the task compared with HC. No significant correlation was detected between brain activation with significant group differences and the severity of depression and negative self-evaluation in FEMDD or HC. The results suggest the involvement of the malfunctioning visual cortex, prefrontal cortex, and insula in the pathophysiology of self-face recognition in FEMDD, which may provide a novel therapeutic target for adults with FEMDD.

Dynamical regional activity in putamen distinguishes bipolar type I depression and unipolar depression.

OBJECTIVES: Intrinsic human brain activity is time-varying and dynamic. However, there is still a lack of knowledge about the dynamic regional activity differences between unipolar depression (UD) and bipolar type I depression (BD-I), and whether their differential pattern can help to distinguish these two patient groups who are prone to misdiagnosis in clinical practice. METHOD: In this study, we used the dynamical fractional amplitude of low-frequency fluctuations (dfALFF) to examine the resting-state dynamical regional activity in 40 BD-I, 42 UD, and 44 healthy controls (HCs). Analysis of covariance was applied to explore the shared and distinct dfALFF pattern among three groups, and machine-learning methods were conducted to classify BD-I from UD by using the detected distinct dfALFF pattern. RESULTS: Compared with HCs, both BD-I and UD exhibited decreased dfALFF temporal variability in the left inferior temporal gyrus. The BD-I showed significantly decreased dfALFF temporal variability in the left putamen compared to UD. By using the dfALFF variability pattern of the left putamen as features, we achieved the 75.61% accuracy and 0.756 area under curve in classifying BD-I from UD. LIMITATIONS: The small sample size of the current study may limit the generalizability of the findings. CONCLUSIONS: The current study demonstrated that the dfALFF temporal variability pattern in the putamen may show a promise as future diagnostic aids for BD-I and UD.

Shared and distinct patterns of dynamical degree centrality in bipolar disorder across different mood states.

Background: Previous studies have probed the brain static activity pattern in bipolar disorder across different states. However, human intrinsic brain activity is time-varying and dynamic. There is a lack of knowledge about the brain dynamical pattern in bipolar disorder across different mood states. Methods: This study used the dynamical degree centrality (dDC) to investigate the resting-state whole-brain dynamical pattern voxel-wise in a total of 62 bipolar disorder [28 bipolar depression (BD), 13 bipolar mania (BM), 21 bipolar euthymia (BE)], and 30 healthy controls (HCs). One-way analysis of variance (ANOVA) was applied to explore the omnibus differences of the dDC pattern across all groups, and Pearson's correlation analysis was used to evaluate the relationship between the dDC variability in detected regions with clinical symptom severity. Results: One-way ANOVA analysis showed the omnibus differences in the left inferior parietal lobule/middle occipital gyrus (IPL/MOG) and right precuneus/posterior cingulate cortex (PCUN/PCC) across all groups. The post hoc analysis revealed that BD showed decreased dDC in the IPL/MOG compared with all other groups, and both BD and BM exhibited decreased dDC in the PCUN/PCC compared with BE and HCs. Furthermore, correlation analysis showed that the dDC variability of the IPL/MOG and PCUN/PCC negatively correlated with the depression symptom levels in all patients with bipolar disorder. Conclusion: This study demonstrated the distinct and shared brain dynamical pattern of the depressive, manic, and euthymia states. Our findings provide new insights into the pathophysiology of bipolar disorder across different mood states from the dynamical brain network pattern perspective.

Aberrant brain dynamics in major depressive disorder with suicidal ideation.

BACKGROUND: Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD). Accumulating studies demonstrated that MDD with SI was associated with static alterations in brain activity and functional connectivity. However, given that brain is a highly dynamic system, the changes of brain dynamic patterns in MDD with SI remain unknown. METHODS: We included 60 MDD patients with SI (MDD-SI), 58 MDD patients without SI (MDD-NSI), and 58 healthy controls (HCs) who underwent resting-state functional magnetic resonance imaging. The sliding-window approach was used to calculate the dynamic fractional amplitude of low-frequency fluctuation (dfALFF) and dynamic degree centrality (dDC) to characterize the temporal dynamic regional activity and distant functional connectivity. We compared dfALFF and dDC across groups and further conducted correlations between abnormal dynamic metrics and the severity of suicidality. RESULTS: In terms of the dynamic regional activity, MDD-SI showed decreased dfALFF in the left lingual gyrus and right middle occipital gyrus compared with MDD-NSI; in terms of the dynamic distant connectivity, MDD-SI showed decreased dDC in the right middle frontal gyrus compared with MDD-NSI. The decreased dDC in the right middle frontal gyrus was correlated with increased severity of suicidality. LIMITATIONS: The relatively small sample size. CONCLUSIONS: We demonstrate the specific brain dynamic patterns of MDD-SI in regional activity and distant functional connectivity compared to MDD-NSI. Especially the decreased temporal variability of the distant connectivity in the middle frontal gyrus was associated with SI. These altered dynamic patterns may represent a potential neurobiological diathesis of SI in MDD.

Decreased integration of default-mode network during a working memory task in schizophrenia with severe attention deficits.

Background: Working memory (WM) and attention deficits are both important features of schizophrenia. WM is closely related to attention, for it acted as an important characteristic in activating and manipulating WM. However, the knowledge of neural mechanisms underlying the relationship between WM and attention deficits in schizophrenia is poorly investigated. Methods: Graph theory was used to examine the network topology at the whole-brain and large-scale network levels among 125 schizophrenia patients with different severity of attention deficits (65 mild attention deficits; 46 moderate attention deficits; and 14 severe attention deficits) and 53 healthy controls (HCs) during an N-back WM task. These analyses were repeated in the same participants during the resting state. Results: In the WM task, there were omnibus differences in small-worldness and normalized clustering coefficient at a whole-brain level and normalized characterized path length of the default-mode network (DMN) among all groups. Post hoc analysis further indicated that all patient groups showed increased small-worldness and normalized clustering coefficient of the whole brain compared with HCs, and schizophrenia with severe attention deficits showed increased normalized characterized path length of the DMN compared with schizophrenia with mild attention deficits and HCs. However, these observations were not persisted under the resting state. Further correlation analyses indicated that the increased normalized characterized path length of the DMN was correlated with more severe attentional deficits and poorer accuracy of the WM task. Conclusion: Our research demonstrated that, compared with the schizophrenia patients with less attention deficits, disrupted integration of the DMN may more particularly underlie the WM deficits in schizophrenia patients with severe attention deficits.

Differential Dynamical Pattern of Regional Homogeneity in Bipolar and Unipolar Depression: A Preliminary Resting-State fMRI Study.

Background: Bipolar depression (BD) and unipolar depression (UD) are both characterized by depressive moods, which are difficult to distinguish in clinical practice. Human brain activity is time-varying and dynamic. Investigating dynamical pattern alterations of depressed brains can provide deep insights into the pathophysiological features of depression. This study aimed to explore similar and different abnormal dynamic patterns between BD and UD. Methods: Brain resting-state functional magnetic resonance imaging data were acquired from 36 patients with BD type I (BD-I), 38 patients with UD, and 42 healthy controls (HCs). Analysis of covariance was adopted to examine the differential pattern of the dynamical regional homogeneity (dReHo) temporal variability across 3 groups, with gender, age, and education level as covariates. Post-hoc analyses were employed to obtain the different dynamic characteristics between any 2 groups. We further applied the machine-learning methods to classify BD-I from UD by using the detected distinct dReHo pattern. Results: Compared with patients with UD, patients with BD-I demonstrated decreased dReHo variability in the right postcentral gyrus and right parahippocampal gyrus. By using the dReHo variability pattern of these two regions as features, we achieved the 91.89% accuracy and 0.92 area under curve in classifying BD-I from UD. Relative to HCs, patients with UD showed increased dReHo variability in the right postcentral gyrus, while there were no dReHo variability differences in patients with BD-I. Conclusions: The results of this study mainly report the differential dynamic pattern of the regional activity between BD-I and UD, particular in the mesolimbic system, and show its promising potential in assisting the diagnosis of these two depression groups.

Weak Association Between the Glutamate Decarboxylase 1 Gene (GAD1) and Schizophrenia in Han Chinese Population.

OBJECTIVES: Schizophrenia (SZ) is a complex psychiatric disorder with high heritability, and genetic components are thought to be pivotal risk factors for this illness. The glutamate decarboxylase 1 gene (GAD1) was hypothesized to be a candidate risk locus for SZ given its crucial role in the GABAergic neurotransmission system, and previous studies have examined the associations of single nucleotide polymorphisms (SNPs) spanning the GAD1 gene with SZ. However, inconsistent results were obtained. We hence examined the associations between GAD1 SNPs and SZ in two independent case-control samples of Han Chinese ancestry. MATERIALS AND METHODS: Two Han Chinese SZ case-control samples, referred as the discovery sample and the replication sample, respectively, were recruited for the current study. The discovery sample comprised of 528 paranoid SZ cases (with age of first onset ≥ 18) and 528 healthy controls; the independent replication sample contained 1,256 early onset SZ cases (with age of first onset < 18) and 2,661 healthy controls. Logistic regression analysis was performed to examine the associations between GAD1 SNPs and SZ. RESULTS: Ten SNPs covering GAD1 gene were analyzed in the discovery sample, and two SNPs showed nominal associations with SZ (rs2241165, P = 0.0181, OR = 1.261; rs2241164, P = 0.0225, OR = 1.219). SNP rs2241164 was also nominally significant in the independent replication sample (P = 0.0462, OR = 1.110), and the significance became stronger in a subsequent meta-analysis combining both discovery and replication samples (P = 0.00398, OR = 1.138). Nevertheless, such association could not survive multiple corrections, although the effect size of rs2241164 was comparable with other SZ risk loci identified in genome-wide association studies (GWAS) in Han Chinese population. We also examined the associations between GAD1 SNPs and SZ in published datasets of SZ GWAS in East Asians and Europeans, and no significant associations were observed. CONCLUSION: We observed weak associations between GAD1 SNPs and risk of SZ in Han Chinese populations. Further analyses in larger Han Chinese samples with more detailed phenotyping are necessary to elucidate the genetic correlation between GAD1 SNPs and SZ.

Behavioral abnormalities and phosphorylation deficits of extracellular signal-regulated kinases 1 and 2 in rat offspring of the maternal immune activation model.

Extracellular signal-regulated kinase (ERK) signal transduction is known to be associated with neurogenesis and neuronal differentiation and as such may be related to the synaptic plasticity associated with cognitive function. Although antipsychotic drug studies have suggested a potential role for the ERK cascade in schizophrenia, the mechanistic basis is unknown. The maternal immune activation (MIA) rat model is a well-known to simulate many of the clinical symptoms of schizophrenia, including cognitive deficits, but a role in this model for dynamic changes in ERK has not been established. In this study, polyinosinic:polycytidylic acid was administered to rats intravenously at a dose of 10 mg/kg on embryonic day 9.5 to produce MIA. The effect of MIA on behavior and ERK phosphorylation within the prefrontal cortex and the hippocampus of adolescent and adult offspring were explored. We also examined neurofilaments, a marker of neurogenesis, which have been reported to be modulated by ERK signaling. The results demonstrate an age- and region-specific profile of ERK expression and phosphorylation and suggest possible relationships among ERK, neurofilament expression, and cognitive performance in schizophrenia.