µ-STAR: A novel framework for spatio-temporal M/EEG source imaging optimized by microstates.

Source imaging of Electroencephalography (EEG) and Magnetoencephalography (MEG) provides a noninvasive way of monitoring brain activities with high spatial and temporal resolution. In order to address this highly ill-posed problem, conventional source imaging models adopted spatio-temporal constraints that assume spatial stability of the source activities, neglecting the transient characteristics of M/EEG. In this work, a novel source imaging method µ-STAR that includes a microstate analysis and a spatio-temporal Bayesian model was introduced to address this problem. Specifically, the microstate analysis was applied to achieve automatic determination of time window length with quasi-stable source activity pattern for optimal reconstruction of source dynamics. Then a user-specific spatial prior and data-driven temporal basis functions were utilized to characterize the spatio-temporal information of sources within each state. The solution of the source reconstruction was obtained through a computationally efficient algorithm based upon variational Bayesian and convex analysis. The performance of the µ-STAR was first assessed through numerical simulations, where we found that the determination and inclusion of optimal temporal length in the spatio-temporal prior significantly improved the performance of source reconstruction. More importantly, the µ-STAR model achieved robust performance under various settings (i.e., source numbers/areas, SNR levels, and source depth) with fast convergence speed compared with five widely-used benchmark models (including wMNE, STV, SBL, BESTIES, & SI-STBF). Additional validations on real data were then performed on two publicly-available datasets (including block-design face-processing ERP and continuous resting-state EEG). The reconstructed source activities exhibited spatial and temporal neurophysiologically plausible results consistent with previously-revealed neural substrates, thereby further proving the feasibility of the µ-STAR model for source imaging in various applications.

Dynamic structure-function coupling across three major psychiatric disorders.

BACKGROUND: Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure-function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ). METHODS: We quantified the dynamic structure-function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure-function coupling with the topological features of functional networks to examine how the structure-function relationship facilitates brain information communication over time. RESULTS: The dynamic structure-function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure-function coupling and the topological features of functional networks are altered in a manner indicative of state specificity. CONCLUSIONS: These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure-function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.

Metagenomic insights into the changes in the rhizosphere microbial community caused by the root-knot nematode Meloidogyne incognita in tobacco.

Root-knot nematode (RKN) disease is a destructive soil disease that affects crop health and causes huge losses in crop production. To explore the relationships between soil environments, rhizobacterial communities, and plant health, rhizosphere bacterial communities were analyzed using metagenomic sequencing in tobacco samples with different grades of RKN disease. The results showed that the community structure and function of the plant rhizosphere were significantly correlated to the RKN disease. RKN density and urease content were key factors affecting the rhizosphere bacterial community. Urease accelerated the catabolism of urea and led to the production of high concentrations of ammonia, which directly suppressed the development of RKNs or by improving the nutritional and growth status of microorganisms that were antagonistic to RKNs. Further experiments showed that the suppression role of ammonia should be attributed to the direct inhibition of NH3. The bacterial members that were positively correlated with RKN density, contained many plant cell wall degrading enzymes, which might destroy plant cell walls and promote the colonization of RKN in tobacco roots. The analysis of metatranscriptome and metabolism demonstrated the role of these cell wall degrading enzymes. This study offers a comprehensive insight into the relationships between RKNs, bacteria, and soil environmental factors and provides new ideas for the biological control of RKNs.

Fungal dynamic changes in naturally fermented 'Kyoho' grape juice.

The 'Kyoho' grape (Vitaceae, Plantae) has large ears, plenty of flesh, and rich nutrition and is planted across a large area in China. There are few reports on this variety in winemaking, especially on the dynamic changes of fungi in the wine fermentation broth. In this study, we used the 'Kyoho' grapes as raw materials and adopted a high throughput to analyze dynamic changes in fungal species composition of the natural fermentation broth at four time points: day 1 (D1P), day 3 (D3P), day 5 (D5P), and day 15 (D15P). Changes in fungal metabolic pathways and dominant yeasts were also analyzed. A total of 78 families, 110 genera, and 137 species were detected, in the natural fermentation broth samples. Forty-nine families, 60 genera, and 72 species were found in the control check (CK). A total of 66 differential metabolic pathways were enriched; of those, 41 were up-regulated compared to CK, such as CDP-diacylglycerol biosynthesis I (PWY 5667), chitin degradation to ethanol (PWY 7118), and the super pathway of phosphatidate biosynthesis (PWY 7411). Changes in fungal metabolic pathways were in line with the dynamic changes of dominant yeast species in the whole process of fermentation. Pichia kluyveri, P. membranifaciens, and Citeromyces matritensis are the dominant species in the later stages of natural fermentation. These yeast species may play vital roles in the 'Kyoho' wine industry in the future.

RACO-1 modulates Hippo signalling in oesophageal squamous cell carcinoma.

Oesophageal cancer is one of the most lethal malignancies worldwide, whereas the 5-year survival is less than 20%. Although the detailed carcinogenic mechanisms are not totally clear, recent genomic sequencing data showed dysregulation of Hippo signalling could be a critical factor for oesophageal squamous cell carcinoma (ESCC) progression. Therefore, understanding of the molecular mechanisms that control Hippo signalling activity is of great importance to improve ESCC diagnostics and therapeutics. Our current study revealed RACO-1 as an inhibitory protein for YAP/TEAD axis. Depletion of RACO-1 increases the protein level of YAP and expression of YAP/TEAD target gene. Besides, RACO-1 silencing could promote ESCC cell invasion and migration, which effect could be rescued by YAP depletion in ESCC cells. Immunoprecipitation showed that RACO-1 associated with YAP and promote ubiquitination and degradation of YAP at k48 poly-ubiquitination site. Our research discovered a new regulator of Hippo signalling via modulating YAP stability. RACO-1 could be a promising factor, which serves cancer diagnostics and therapeutics in ESCC patients.

APOA5 rs651821 confers increased risk for hypertension in Tongdao Dong population.

Hypertension is a complex disease that partially influenced by genetic factors. Up till now, the association between the rs651821 in apolipoprotein A5 (APOA5) gene and hypertension remains unknown. This study was undertaken to investigate the relationship between the APOA5 rs651821 and hypertension in Tongdao Dong population. A total of 274 participants were involved in this study (135 hypertensive patients and 139 nonhypertensive adults). The single nucleotide polymorphism (SNP) was genotyped by using polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP). The results showed that the genotypic and allelic frequencies of rs651821 were significantly different between the normotensives and hypertensive subjects (P = 0.009, P = 0.003 respectively). TC/CC genotypes of rs651821 were associated with an elevated risk of hypertension (TC/CC vs. TT: adjusted odds ratio (AOR) = 1.791, 95%CI = 1.067-3.006, P = 0.009). Besides, the TC/CC genotypes were related to an increased plasma triglyceride (TG) level (TC/CC vs. TT: 2.47 ± 1.91 vs. 1.82 ± 1.07, P = 0.001).The results suggest that the C carriers of APOA5 rs651821 are associated with an increased serum TG concentration and may cause the increased susceptibility of the individual to hypertension in Chinese Dong population.

Composite Dietary Antioxidant Index is inversely associated with visceral adipose tissue area among U.S. adults: A cross-sectional study.

Obesity is becoming a global health problem. Visceral adiposity is the main cause of metabolic and cardiovascular diseases. Dietary improvement is the key to controlling obesity. We hypothesized that a higher Composite Dietary Antioxidant Index (CDAI) was associated with a lower visceral adipose tissue (VAT) area. In this cross-sectional study, 10,389 adults were selected from the National Health and Nutrition Examination Survey 2011-2018. CDAI was calculated based on 6 micronutrients: zinc, selenium, total carotenoids, vitamin A, vitamin C, and vitamin E. VAT area was determined by the dual-energy X-ray absorptiometry scan. Linear regression models were constructed to evaluate the association between CDAI and VAT area. Subgroup analyses were also performed. The mean age of participants was 39.68 years, 5240 were male, and 3841 of those were non-Hispanic White. The inverse associations were observed in all models. In model 3, CDAI was inversely associated with VAT area as a continuous variable, ß (95% confidence interval), -0.56 (-0.85 to -0.27). When compared with the first tertile, the third tertile of CDAI was also inversely associated with VAT area, ß (95% confidence interval), -6.72 (-10.44 to -2.99). No interactions were found in the subgroup analyses. In conclusion, an inverse association between CDAI and VAT area was found among U.S. adults aged 20 to 59 years. These results suggest the possible benefit of an antioxidant diet in relieving visceral obesity. More prospective studies are needed to identify this dietary benefit.

THRIVE, ASTRAL, and iScore scales for predicting prognosis of mechanical thrombectomy in patients with acute ischemic stroke.

OBJECTIVE: To validate the predictive performance of the THRIVE, ASTRAL, and iScore scales for clinical functional outcomes following mechanical thrombectomy (MT) for acute ischemic stroke (AIS). METHODS: A total of 111 patients meeting the inclusion criteria were included in this study, with 59 (53.2%) having a good prognosis and 52 (46.8%) having a poor prognosis. MedCalc software was applied to plot receiver operating characteristic (ROC) curves, calculate the area under the curve (AUC), and compare the predictive efficacy of the three scales two by two using Delong text. Statistical significance was defined as Pc < 0.05. RESULTS: Logistic binary regression multifactorial analysis revealed that iScore is one of the poor predictors of prognosis in patients with MT. The AUC values for the THRIVE, ASTRAL, and iScore scales in predicting prognosis after MT were found to be 0.713, 0.738, and 0.820, respectively. CONCLUSION: The iScore is a reliable tool for assessing the poor prognosis of MT in patients with AIS.

Clinical study of the prognostic value of the Essen score for acute cerebral infarction.

OBJECTIVE: A few clinical studies have been conducted on the prognostic value of the Essen score in acute cerebral infarction (ACI), and this study explores whether the Essen score can assess the prognosis of ACI. METHODS: Data were collected from 1176 patients with ACI. The patients were divided into three groups on the basis of the Essen score, with groups 1, 2 and 3 having scores of 0-2, 3-6 and 7-9, respectively. Logistic multivariate analysis was performed to analyse the predictors of poor prognosis in patients with ACI. The X2 trend test was used to compare the poor-prognosis groups on the basis of the Essen score. The receiver operating characteristic (ROC) curve of patient prognosis was plotted using MedCalc software, and the area under the ROC curve (AUC) was calculated. P < 0.05 was considered statistically significant. RESULTS: Multivariate analysis of the good- and poor-prognosis groups of ACI showed that the Essen score and the male gender were predictors of poor prognosis. The X2 trend test was used to compare the poor-prognosis groups on the basis of the Essen score, and results suggested that the higher the Essen score was, the worse the prognosis was. The Essen score assessed the prognosis of ACI with an AUC of 0.787 and P < 0.001. CONCLUSION: The Essen score is a valuable scoring system for predicting the prognosis of patients with ACI.

Barthel Index, SPAN-100, and NIHSS Studies on the Predictive Value of Prognosis in Patients With Thrombolysis.

OBJECTIVE: We mainly explore the predictive value of Barthel Index (BI), SPAN-100, and National Institute of Health stroke scale (NIHSS) scores on clinical prognosis and functional outcomes in thrombolytic patients and compare the differences in the predictive values of the above 3 scales so as to provide an effective basis to evaluate the prognosis of thrombolytic patients. METHODS: Data were collected from 212 patients with the first-onset AIS (acute ischemic stroke). The enrolled patients were treated with recombinant tissue plasminogen activator thrombolytic therapy and were divided into 2 groups according to the modified Rankin Scale (mRS) score at discharge: the prognosis group (mRS≤2 points) and the poor prognosis group (mRS≥3 points). Logistic multivariate analysis was used to analyze the predictors of poor prognosis in patients with thrombolysis. MedCalc software was used to plot receiver operating characteristic (ROC) curves, calculate the area under the ROC curve (AUC), and compare the prediction performance of the 3 scales by the Delong and colleagues' method, and the difference of P <0.05 was statistically significant. RESULTS: Logistic binary regression multivariate analysis suggested that BI was a predictor of poor prognosis for thrombolytic therapy in patients with AIS. The lower the BI score, the poorer the prognosis. The AUC for BI score was 0.862, 95% CI (0.808-0.906), NIHSS score AUC was 0.665, 95% CI (0.597-0.728), and SPAN-100 score AUC was 0.640, 95% CI (0.572-0.705). AUC comparison of 3 scoring ROC curves suggested statistically significant differences between BI and NIHSS ( PC =0.0000), BI and SPAN-100 ( PC =0.0000); no significant difference was observed between SPAN-100 and NIHSS ( PC =1.7997). CONCLUSIONS: Simple BI scores have a high prognostic value for thrombolytic therapy in AIS.

Association of post-intervention pressure gradient with symptom-free at 6 months in idiopathic intracranial hypertension with venous sinus stenosis treated by stenting.

OBJECTIVE: This study aimed to identify the key factors that might affect the clinical outcome of patients with idiopathic intracranial hypertension (IIH) and Venous sinus stenting (VSS). METHODS: We performed an analysis of a prospectively collected database of patients with IIH and VSS who underwent stenting. The trans-stenotic pressure gradient was measured before and after intervention. In additional, patients' baseline characteristics, procedure details and clinical outcomes at 6-month follow-up (including changes in headache, visual impairment, papilledema, etc.) were recorded. The effects of post-intervention pressure gradient on symptom-free at 6 months were explored using logistic regression analysis, generalized additive model and receiver operator characteristic (ROC) curve. RESULTS: Of 101 patients included in this study, the median pressure gradient across stenosis decreased from 19 mmHg before intervention to 2 mmHg after intervention. At 6 months, symptom-free was observed in 58 cases (57.4%). Multivariable logistic analysis and generalized additive model showed that post-intervention pressure gradient (increased by 1 mmHg) was independently and linearly correlated with symptom-free (OR = 0.79, 95% CI = 0.67-0.94). Moreover, the post-intervention pressure gradient revealed moderate discrimination with an area under ROC curve of 0.68 (95% CI = 0.57-0.78). Similar associations were observed for the disappearance of headache and papilledema, but not for the visual recovery. CONCLUSION: The post-intervention pressure gradient may be a valid and reliable predictor of 6-month clinical outcome in patients with IIH and VSS treated by stenting. Nevertheless, external validation with blinded outcome is still needed to confirm its performance before clinical application.

Comparison of microcatheter and pressure wire for venous sinus manometric evaluation of patients with idiopathic intracranial hypertension.

BACKGROUND: Venous sinus manometry performed by microcatheter to assess candidacy for venous sinus stenting in patients with idiopathic cranial pressure (IIH) can be tiring, time-consuming and unreliable. Pressure wire is widely used to measure coronary pressure and evaluate coronary stenosis severity, but venous sinus manometry using the pressure guide wire has only been reported in one case, and few studies have examined the accuracy of this approach. OBJECTIVE: To compare venous manometry performed by microcatheter with by pressure wire under awake setting in patients with IIH. METHODS: The manometry results of 30 patients with IIH were recorded by Rebar-27 microcatheter and a pressure wire under awake setting. The mean venous pressures (MVPs) and trans-stenosis pressure gradients were obtained and compared between microcatheter and pressure wire. Paired t-test) were used to evaluate the data between the two groups. RESULTS: MVPs in superior sagittal sinus (SSS) and torcula were slightly higher with microcatheter, though without statistically significant differences (p > 0.05). MVPs in transverse sinus (TS) and sigmoid sinus (SS) were significantly higher with microcatheter (p < 0.05). Trans-stenotic pressure gradient with microcatheter was significantly higher than with pressure wire (p＜0.001). CONCLUSIONS: Intracranial venous pressure measured with the microcatheter and pressure wire showed a moderate difference. Compared with the traditional microcatheter method，the pressure wire is safe, fast and effective method to identify the patient needing intervention.

Brain network analysis reveals convergent and divergent aberrations between mild stroke patients with cortical and subcortical infarcts during cognitive task performing.

Although consistent evidence has revealed that cognitive impairment is a common sequela in patients with mild stroke, few studies have focused on it, nor the impact of lesion location on cognitive function. Evidence on the neural mechanisms underlying the effects of mild stroke and lesion location on cognitive function is limited. This prompted us to conduct a comprehensive and quantitative study of functional brain network properties in mild stroke patients with different lesion locations. Specifically, an empirical approach was introduced in the present work to explore the impact of mild stroke-induced cognitive alterations on functional brain network reorganization during cognitive tasks (i.e., visual and auditory oddball). Electroencephalogram functional connectivity was estimated from three groups (i.e., 40 patients with cortical infarctions, 48 patients with subcortical infarctions, and 50 healthy controls). Using graph theoretical analysis, we quantitatively investigated the topological reorganization of functional brain networks at both global and nodal levels. Results showed that both patient groups had significantly worse behavioral performance on both tasks, with significantly longer reaction times and reduced response accuracy. Furthermore, decreased global and local efficiency were found in both patient groups, indicating a mild stroke-related disruption in information processing efficiency that is independent of lesion location. Regarding the nodal level, both divergent and convergent node strength distribution patterns were revealed between both patient groups, implying that mild stroke with different lesion locations would lead to complex regional alterations during visual and auditory information processing, while certain robust cognitive processes were independent of lesion location. These findings provide some of the first quantitative insights into the complex neural mechanisms of mild stroke-induced cognitive impairment and extend our understanding of underlying alterations in cognition-related brain networks induced by different lesion locations, which may help to promote post-stroke management and rehabilitation.

Characterizing the penumbras of white matter hyperintensities in patients with cerebral small vessel disease.

PURPOSE: The white matter hyperintensity penumbra (WMH-P) is the subtly changed normal-appearing white matter (NAWM) that surrounds white matter hyperintensities (WMHs). The goal of this study was to define WMH-P in cerebral small vessel disease (CSVD) by arterial spin labeling (ASL) and diffusion tensor imaging (DTI)/diffusion kurtosis imaging (DKI). MATERIALS AND METHODS: We prospectively analyzed 42 patients with CSVD. To determine the range of cerebral blood flow (CBF) and DTI/DKI penumbras around white matter hyperintensities, we generated NAWM layer masks from periventricular WMHs (PVWMHs) and deep WMHs (DWMHs). Mean values of CBF, fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis, and radial kurtosis within the WMHs and their corresponding NAWM layer masks were analyzed. Paired sample t tests were used for analysis, and differences were considered statistically significant if the associated p value was ≤ 0.05. RESULTS: For DWMHs, the CBF penumbras were 13 mm, and the DTI/DKI penumbras were 8 mm. For PVWMHs, the CBF penumbras were 14 mm, and the DTI/DKI penumbras were 14 mm. CONCLUSIONS: Our findings revealed that DTI/DKI and ASL can show structural and blood flow changes in brain tissue surrounding WMHs. In DWMHs, the blood flow penumbra was larger than the structural penumbra, while in PVWMHs, the blood flow penumbra was almost the same as the structural penumbra.

Machine Learning Techniques Reveal Aberrated Multidimensional EEG Characteristics in Patients with Depression.

Depression has become one of the most common mental illnesses, causing serious physical and mental harm. However, there remain unclear and uniform physiological indicators to support the diagnosis of clinical depression. This study aimed to use machine learning techniques to investigate the abnormal multidimensional EEG features in patients with depression. Resting-state EEG signals were recorded from 41 patients with depression and 34 healthy controls. Multiple dimensional characteristics were extracted, including power spectral density (PSD), fuzzy entropy (FE), and phase lag index (PLI). These three different dimensional characteristics with statistical differences between two groups were ranked by three machine learning algorithms. Then, the ranked characteristics were placed into the classifiers according to the importance of features to obtain the optimal feature subset with the highest classification accuracy. The results showed that the optimal feature subset contained 86 features with the highest classification accuracy of 98.54% ± 0.21%. According to the statistics of the optimal feature subset, PLI had the largest number of features among the three categories, and the number of beta features was bigger than other rhythms. Moreover, compared to the healthy controls, the PLI values in the depression group increased in theta and beta rhythms, but decreased in alpha1 and alpha2 rhythms. The PSD of theta and beta rhythms were significantly greater in depression group than that in healthy controls, and the FE of beta rhythm showed the same trend. These findings indicate that the distribution of abnormal multidimensional features is potentially useful for the diagnosis of depression and understanding of neural mechanisms.

Individualized Prediction of Task Performance Decline Using Pre-Task Resting-State Functional Connectivity.

As a common complaint in contemporary society, mental fatigue is a key element in the deterioration of the daily activities known as time-on-task (TOT) effect, making the prediction of fatigue-related performance decline exceedingly important. However, conventional group-level brain-behavioral correlation analysis has the limitation of generalizability to unseen individuals and fatigue prediction at individual-level is challenging due to the significant differences between individuals both in task performance efficiency and brain activities. Here, we introduced a cross-validated data-driven analysis framework to explore, for the first time, the feasibility of utilizing pre-task idiosyncratic resting-state functional connectivity (FC) on the prediction of fatigue-related task performance degradation at individual level. Specifically, two behavioral metrics, namely ∆RT (between the most vigilant and fatigued states) and TOTslope over the course of the 15-min sustained attention task, were estimated among three sessions from 37 healthy subjects to represent fatigue-related individual behavioral impairment. Then, a connectome-based prediction model was employed on pre-task resting-state FC features, identifying the network-related differences that contributed to the prediction of performance deterioration. As expected, prominent populational TOT-related performance declines were revealed across three sessions accompanied with substantial inter-individual differences. More importantly, we achieved significantly high accuracies for individualized prediction of both TOT-related behavioral impairment metrics using pre-task neuroimaging features. Despite the distinct patterns between both behavioral metrics, the identified top FC features contributing to the individualized predictions were mainly resided within/between frontal, temporal and parietal areas. Overall, our results of individualized prediction framework extended conventional correlation/classification analysis and may represent a promising avenue for the development of applicable techniques that allow precaution of the TOT-related performance declines in real-world scenarios.

PAK4-relevant proliferation reduced by cell autophagy via p53/mTOR/p-AKT signaling.

Background: P21-activated kinase 4 (PAK4) involves in cell proliferation in cancer and mutually regulates with p53, a molecule is demonstrated to control cell autophagy by mammalian target of rapamycin (mTOR)/protein kinase B (AKT) signaling. Since the signaling exhibits an association with PAK family members in cell autophagy, it implies that PAK4-relevant proliferation may be impacted by autophagy via p53 with a lack of evidence in cancer cells. Methods: In this research, transient and stable PAK4-knockdown human hepatocarcinoma cell lines (HepG2) were constructed by transfection of PAK4-RNA interference (RNAi) plasmid and lentivirus containing PAK4-RNAi plasmid, respectively. We investigated cell proliferation using methyl thiazolyl tetrazolium (MTT) and Cell Counting Kit 8 (CCK8) assays, cell cycle by flow cytometry (FCM) and cell autophagy by monodansylcadaverine (MDC) staining and autophagic biomarker's expression, and detected the expressions of p53, mTOR, phosphorylated-AKT (p-AKT) and AKT by immunofluorescence and western blot to explore the mechanism. Results: We successfully constructed transient and stable PAK4-knockdown HepG2 cell lines, and detected dysfunction of the cells' proliferation. An increased expression of p53, as a molecule of cell-cycle-surveillance on G1/S phase, was demonstrated in the cells although the cell cycle blocked at G2/M. And then, we detected increased autophagosome and autophagic biomarker LC3-II, and decreased expressions in p-AKT and mTOR. Conclusions: The proliferation is reduced in PAK4-knockdown HepG2 cells, which is relative to not only cell cycle arrest but also cell autophagy, and p53/mTOR/p-AKT signaling involves in the cell progress. The findings provide a new mechanism on PAK4 block in cancer therapy.

Brain Network Reorganization During Visual Search Task Revealed by a Network Analysis of Fixation-Related Potential.

Visual search is ubiquitous in daily life and has attracted substantial research interest over the past decades. Although accumulating evidence has suggested complex neurocognitive processes underlying visual search, the neural communication across the brain regions remains poorly understood. The present work aimed to fill this gap by investigating functional networks of fixation-related potential (FRP) during the visual search task. Multi-frequency electroencephalogram (EEG) networks were constructed from 70 university students (male/female = 35/35) using FRPs time-locked to target and non-target fixation onsets, which were determined by concurrent eye-tracking data. Then graph theoretical analysis (GTA) and a data-driven classification framework were employed to quantitatively reveal the divergent reorganization between target and non-target FRPs. We found distinct network architectures between target and non-target mainly in the delta and theta bands. More importantly, we achieved a classification accuracy of 92.74% for target and non-target discrimination using both global and nodal network features. In line with the results of GTA, we found that the integration corresponding to target and non-target FRPs significantly differed, while the nodal features contributing most to classification performance primarily resided in the occipital and parietal-temporal areas. Interestingly, we revealed that females exhibited significantly higher local efficiency in delta band when focusing on the search task. In summary, these results provide some of the first quantitative insights into the underlying brain interaction patterns during the visual search process.

Comprehensive analysis reveals potential therapeutic targets and an integrated risk stratification model for solitary fibrous tumors.

Solitary fibrous tumors (SFTs) are rare mesenchymal tumors with unpredictable evolution and with a recurrence or metastasis rate of 10-40%. Current medical treatments for relapsed SFTs remain ineffective. Here, we identify potential therapeutic targets and risk factors, including IDH1 p.R132S, high PD-L1 expression, and predominant macrophage infiltration, suggesting the potential benefits of combinational immune therapy and targeted therapy for SFTs. An integrated risk model incorporating mitotic count, density of Ki-67+ cells and CD163+ cells, MTOR mutation is developed, applying a discovery cohort of 101 primary non-CNS patients with negative tumor margins (NTM) and validated in three independent cohorts of 210 SFTs with the same criteria, and in 36 primary CNS SFTs with NTM. Compared with the existing models, our model shows significantly improved efficacy in identifying high-risk primary non-CNS and CNS SFTs with NTM for tumor progression.Our findings hold promise for advancing therapeutic strategies and refining risk prediction in SFTs.

The complete chloroplast genome of Callianthe picta (Malvaceae).

Callianthe picta likes a warm and humid climate, is resistant to barrenness, and is easy to reproduce. Its petals and leaves can promote blood circulation and remove blood stasis, and can also be used to relax the muscles and collaterals. In this study, we sequenced the complete chloroplast genome sequence of C. picta to investigate its phylogenetic relationship in the family Abutilon. The complete chloroplast size of C. picta is 160,398 bp, including a large single-copy (LSC) region of 89,088 bp, a small single-copy (SSC) region of 20,138 bp, a pair of invert repeats (IRs) regions of 25,586 bp. The GC content of the whole complete chloroplast genome is 37.0%. We annotated 128 genes in the genome in detail, including 84 protein-coding genes, 36 tRNA genes, and 8 rRNA genes. Phylogenetic analysis indicated that C. picta was closely related to Abutilon theophrati.