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Tumor necrosis factor-α (TNF-α) polymorphisms may influence dyslipidemia, but their role remains unclear. This case-control study investigated associations between TNF-α gene polymorphisms (-1031T/C, -863C/A, -857C/T, -308G/A, and -238G/A) and dyslipidemia in 595 participants (162 cases, 433 controls) from the Chaoshan region of China. Anthropometric, biochemical, and genetic data were analyzed using Chi-squared tests and logistic regression, with the false discovery rate (FDR) method applied to correct for multiple comparisons. Results revealed that only the -1031T/C and -863C/A polymorphisms were significantly associated with dyslipidemia. Carriers of the TC+CC genotype for -1031T/C (odds ratio [OR]=0.48, 95% CI: 0.30-0.78, PFDR=0.006) and the CA+AA genotype for -863C/A (OR=0.41, 95% CI: 0.24-0.70, PFDR=0.004) had lower odds of dyslipidemia. Protective effects were observed for the C allele at -1031T/C (OR=0.58, PFDR=0.012) and the A allele at -863C/A (OR=0.47, PFDR=0.004). Stratified analyses showed that these associations were significant in males but not females. Functional annotation linked these TNF-α gene polymorphisms to transcription factors (e.g., HNF-1A, STAT1β) in the adipogenesis pathway. This study reveals genetic associations between TNF-α polymorphisms and dyslipidemia, particularly in males, and provides mechanistic insights into their role in transcriptional regulation.
We presented an attosecond-precision timing detector based on linear optics. The minimum measurement floor is 1×10–10 fs2/Hz with only 1 mW input optical power. With this novel technique, the residual dispersion of a 5.2 km fiber link is characterized and precisely compensated. Finally, a comprehensive feedback model has been developed to analyze the noise coupling in a long-distance link stabilization system. The simulation results demonstrate an out-of-loop jitter of merely 359 as, integrated at [1 Hz, 1 MHz], at 1 mW input power per photodetector of our timing detector. Remarkably, the system is capable of maintaining sub-femtosecond precision even at optical power levels as low as 240 nW (for a 5.2 km link length), or link lengths as long as 20 km (with 1 μW optical power), respectively.
Machine learning (ML) models have been developed to identify randomised controlled trials (RCTs) to accelerate systematic reviews (SRs). However, their use has been limited due to concerns about their performance and practical benefits. We developed a high-recall ensemble learning model using Cochrane RCT data to enhance the identification of RCTs for rapid title and abstract screening in SRs and evaluated the model externally with our annotated RCT datasets. Additionally, we assessed the practical impact in terms of labour time savings and recall improvement under two scenarios: ML-assisted double screening (where ML and one reviewer screened all citations in parallel) and ML-assisted stepwise screening (where ML flagged all potential RCTs, and at least two reviewers subsequently filtered the flagged citations). Our model achieved twice the precision compared to the existing SVM model while maintaining a recall of 0.99 in both internal and external tests. In a practical evaluation with ML-assisted double screening, our model led to significant labour time savings (average 45.4%) and improved recall (average 0.998 compared to 0.919 for a single reviewer). In ML-assisted stepwise screening, the model performed similarly to standard manual screening but with average labour time savings of 74.4%. In conclusion, compared with existing methods, the proposed model can reduce workload while maintaining comparable recall when identifying RCTs during the title and abstract screening stages, thereby accelerating SRs. We propose practical recommendations to effectively apply ML-assisted manual screening when conducting SRs, depending on reviewer availability (ML-assisted double screening) or time constraints (ML-assisted stepwise screening).
Although it is well established that gestational diabetes mellitus (GDM) is associated with fetal overgrowth in singleton pregnancies, little is known about its role in twins. We aimed to explore the relationship between GDM and the longitudinal fetal growth in twin pregnancies. This was a retrospective matched cohort study of GDM and non-GDM twin pregnancies delivered ≥36 weeks without other complications. All the women performed ≥3 ultrasounds after 22 weeks. Linear mixed models (LMMs) were used to explore the relationships between longitudinal fetal growth trajectories and GDM. Group-based trajectory modeling (GBTM) and generalized estimating equation (GEE) were applied to identify the latent growth patterns and investigate their relationships with GDM. In total, 215 GDM and 645 non-GDM twins were included, the majority of the patients did not require medication therapy (n = 202, GDMA1). LMM revealed that, compared with non-GDM, GDM was associated with an average increase in fetal weight of 4.36 g (95% CI [1.25, 7.48]) per week. GBTM and GEE further revealed that GDM increased the odds of fetal weight trajectory to nearly 40% of the total fetal weight trajectory, classified into the high-speed group (aOR = 1.39, 95% CI [1.03, 1.88]), associating with a 49.44 g (95% CI [11.41, 87.48]) increase in birth weight. Subgroup analysis revealed that all these differences were only significant among the GDMA1 pregnancies (p < .05). GDM (GDMA1) is significantly associated with an increase in fetal weight during gestation in twin pregnancies. However, this acceleration is mild, and its significance requires further exploration.
We demonstrated a method to improve the output performance of a Ti:sapphire laser in the long-wavelength low-gain region with an efficient stimulated Raman scattering process. By shifting the wavelength of the high-gain-band Ti:sapphire laser to the long-wavelength low-gain region, high-performance Stokes operation was achieved in the original long-wavelength low-gain region of the Ti:sapphire laser. With the fundamental wavelength tuning from 870 to 930 nm, first-order Stokes output exceeding 2.5 W was obtained at 930–1000 nm, which was significantly higher than that directly generated by the Ti:sapphire laser, accompanied by better beam quality, shorter pulse duration and narrower linewidth. Under the pump power of 42.1 W, a maximum first-order Stokes power of 3.24 W was obtained at 960 nm, with a conversion efficiency of 7.7%. Furthermore, self-mode-locked modulations of first- and second-order Stokes generation were observed in Ti:sapphire intracavity solid Raman lasers for the first time.
Mythimna separata (Lepidoptera: Noctuidae) is an omnivorous pest that poses a great threat to food security. Insect antimicrobial peptides (AMPs) are small peptides that are important effector molecules of innate immunity. Here, we investigated the role of the AMP cecropin B in the growth, development, and immunity of M. separata. The gene encoding M. separata cecropin B (MscecropinB) was cloned. The expression of MscecropinB was determined in different developmental stages and tissues of M. separata. It was highest in the prepupal stage, followed by the pupal stage. Among larval stages, the highest expression was observed in the fourth instar. Tissue expression analysis of fourth instar larvae showed that MscecropinB was highly expressed in the fat body and haemolymph. An increase in population density led to upregulation of MscecropinB expression. MscecropinB expression was also upregulated by the infection of third and fourth instar M. separata with Beauveria bassiana or Bacillus thuringiensis (Bt). RNA interference (RNAi) targeting MscecropinB inhibited the emergence rate and fecundity of M. separata, and resulted in an increased sensitivity to B. bassiana and Bt. The mortality of M. separata larvae was significantly higher in pathogen plus RNAi-treated M. separata than in controls treated with pathogens only. Our findings indicate that MscecropinB functions in the eclosion and fecundity of M. separata and plays an important role in resistance to infection by B. bassiana and Bt.
With advancements in cancer treatments, the survival rates of patients with their first primary cancer (FPC) have increased, resulting in a rise in the number of patients with second primary cancer (SPC). However, there has been no assessment on the incidence of suicide among patients with SPC. This study assessed the occurrence of suicide among patients with SPC and compared them with that in patients with FPC.
Methods
This was a retrospective, population-based cohort study that followed patients with FPC and SPC diagnosed from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) 17 registries database between 1 January 2000 and 31 December 2019.
Results
For patients with SPC, an age of 85+ years at diagnosis was associated with a higher incidence of suicide death (HR, 1.727; 95% CI, 1.075–2.774), while the suicide death was not considerably different in the chemotherapy group (P > 0.05). Female genital system cancers (HR, 3.042; 95% CI, 1.819–6.361) accounted for the highest suicide death among patients with SPC. The suicide death distribution of patients with SPC over time indicated that suicide events mainly occurred within 5 to 15 years of diagnosis. Compared with patients with FPC, patients with SPC in general had a lower risk of suicide, but increased year by year.
Conclusion
The risk of suicide was reduced in patients with SPC compared with patients with FPC, but increased year by year. Therefore, oncologists and related health professionals need to provide continuous psychological support to reduce the incidence of suicide. The highest suicide death was found among patients with female genital system cancer.
Depression is a debilitating mental disorder that often coexists with anxiety. The genetic mechanisms of depression and anxiety have considerable overlap, and studying depression in non-anxiety samples could help to discover novel gene. We assess the genetic variation of depression in non-anxiety samples, using genome-wide association studies (GWAS) and linkage disequilibrium score regression (LDSC).
Methods
The GWAS of depression score and self-reported depression were conducted using the UK Biobank samples, comprising 99,178 non-anxiety participants with anxiety score <5 and 86,503 non-anxiety participants without self-reported anxiety, respectively. Replication analysis was then performed using two large-scale GWAS summary data of depression from Psychiatric Genomics Consortium (PGC). LDSC was finally used to evaluate genetic correlations with 855 health-related traits based on the primary GWAS.
Results
Two genome-wide significant loci for non-anxiety depression were identified: rs139702470 (p = 1.54 × 10−8, OR = 0.29) locate in PIEZO2, and rs6046722 (p = 2.52 × 10−8, OR = 1.09) locate in CFAP61. These associated genes were replicated in two GWAS of depression from PGC, such as rs1040582 (preplication GWAS1 = 0.02, preplication GWAS2 = 2.71 × 10−3) in CFAP61, and rs11661122 (preplication GWAS1 = 8.16 × 10−3, preplication GWAS2 = 8.08 × 10−3) in PIEZO2. LDSC identified 19 traits genetically associated with non-anxiety depression (p < 0.001), such as marital separation/divorce (rg = 0.45, SE = 0.15).
Conclusions
Our findings provide novel clues for understanding of the complex genetic architecture of depression.
Gut microbiome and dietary patterns have been suggested to be associated with depression/anxiety. However, limited effort has been made to explore the effects of possible interactions between diet and microbiome on the risks of depression and anxiety.
Methods
Using the latest genome-wide association studies findings in gut microbiome and dietary habits, polygenic risk scores (PRSs) analysis of gut microbiome and dietary habits was conducted in the UK Biobank cohort. Logistic/linear regression models were applied for evaluating the associations for gut microbiome-PRS, dietary habits-PRS, and their interactions with depression/anxiety status and Patient Health Questionnaire (PHQ-9)/Generalized Anxiety Disorder-7 (GAD-7) score by R software.
Results
We observed 51 common diet–gut microbiome interactions shared by both PHQ score and depression status, such as overall beef intake × genus Sporobacter [hurdle binary (HB)] (PPHQ = 7.88 × 10−4, Pdepression status = 5.86 × 10−4); carbohydrate × genus Lactococcus (HB) (PPHQ = 0.0295, Pdepression status = 0.0150). We detected 41 common diet–gut microbiome interactions shared by GAD score and anxiety status, such as sugar × genus Parasutterella (rank normal transformed) (PGAD = 5.15 × 10−3, Panxiety status = 0.0347); tablespoons of raw vegetables per day × family Coriobacteriaceae (HB) (PGAD = 6.02 × 10−4, Panxiety status = 0.0345). Some common significant interactions shared by depression and anxiety were identified, such as overall beef intake × genus Sporobacter (HB).
Conclusions
Our study results expanded our understanding of how to comprehensively consider the relationships for dietary habits–gut microbiome interactions with depression and anxiety.
Understanding factors associated with post-discharge sleep quality among COVID-19 survivors is important for intervention development.
Aims
This study investigated sleep quality and its correlates among COVID-19 patients 6 months after their most recent hospital discharge.
Method
Healthcare providers at hospitals located in five different Chinese cities contacted adult COVID-19 patients discharged between 1 February and 30 March 2020. A total of 199 eligible patients provided verbal informed consent and completed the interview. Using score on the single-item Sleep Quality Scale as the dependent variable, multiple linear regression models were fitted.
Results
Among all participants, 10.1% reported terrible or poor sleep quality, and 26.6% reported fair sleep quality, 26.1% reported worse sleep quality when comparing their current status with the time before COVID-19, and 33.7% were bothered by a sleeping disorder in the past 2 weeks. After adjusting for significant background characteristics, factors associated with sleep quality included witnessing the suffering (adjusted B = −1.15, 95% CI = −1.70, −0.33) or death (adjusted B = −1.55, 95% CI = −2.62, −0.49) of other COVID-19 patients during hospital stay, depressive symptoms (adjusted B = −0.26, 95% CI = −0.31, −0.20), anxiety symptoms (adjusted B = −0.25, 95% CI = −0.33, −0.17), post-traumatic stress disorders (adjusted B = −0.16, 95% CI = −0.22, −0.10) and social support (adjusted B = 0.07, 95% CI = 0.04, 0.10).
Conclusions
COVID-19 survivors reported poor sleep quality. Interventions and support services to improve sleep quality should be provided to COVID-19 survivors during their hospital stay and after hospital discharge.
Depressive symptoms and cognitive impairment often coexisted in the elderly. This study investigates the effect of late-life depressive symptoms on risk of mild cognitive impairment (MCI).
Methods
A total of 14,231 dementia- and MCI free participants aged 60+ from the Survey of Health, Ageing, and Retirement in Europe were followed-up for 10 years to detect incident MCI. MCI was defined as 1.5 standard deviation (SD) below the mean of the standardized global cognition score. Depressive symptoms were assessed by a 12-item Europe-depression scale (EURO-D). Severity of depressive symptoms was grouped as: no/minimal (score 0–3), moderate (score 4–5), and severe (score 6–12). Significant depressive symptoms (SDSs) were defined as EURO-D score ≥ 4.
Results
During an average of 8.2 (SD = 2.4)-year follow-up, 1,352 (9.50%) incident MCI cases were identified. SDSs were related to higher MCI risk (hazard ratio [HR] = 1.26, 95% confidence intervals [CI]: 1.10–1.44) in total population, individuals aged 70+ (HR = 1.35, 95% CI: 1.14–1.61) and women (HR = 1.28, 95% CI: 1.08–1.51) in Cox proportional hazard model adjusting for confounders. In addition, there was a dose–response association between the severity of depressive symptoms and MCI incidence in total population, people aged ≥70 years and women (p-trend <0.001).
Conclusions
Significant depressive symptoms were associated with higher incidence of MCI in a dose–response fashion, especially among people aged 70+ years and women. Treating depressive symptoms targeting older population and women may be effective in preventing MCI.
China accounts for 17% of the global disease burden attributable to mental, neurological and substance use disorders. As a country undergoing profound societal change, China faces growing challenges to reduce the disease burden caused by psychiatric disorders. In this review, we aim to present an overview of progress in neuroscience research and clinical services for psychiatric disorders in China during the past three decades, analysing contributing factors and potential challenges to the field development. We first review studies in the epidemiological, genetic and neuroimaging fields as examples to illustrate a growing contribution of studies from China to the neuroscience research. Next, we introduce large-scale, open-access imaging genetic cohorts and recently initiated brain banks in China as platforms to study healthy brain functions and brain disorders. Then, we show progress in clinical services, including an integration of hospital and community-based healthcare systems and early intervention schemes. We finally discuss opportunities and existing challenges: achievements in research and clinical services are indispensable to the growing funding investment and continued engagement in international collaborations. The unique aspect of traditional Chinese medicine may provide insights to develop a novel treatment for psychiatric disorders. Yet obstacles still remain to promote research quality and to provide ubiquitous clinical services to vulnerable populations. Taken together, we expect to see a sustained advancement in psychiatric research and healthcare system in China. These achievements will contribute to the global efforts to realize good physical, mental and social well-being for all individuals.
The late Palaeozoic Yong’an–Meizhou depression belt is an important iron (Fe) and polymetallic metallogenic belt in southern China. It has undergone a transformation from Tethys to the circum-Pacific tectonic domain. The Luoyang deposit is one of the typical Fe skarn deposits in the Yong’an–Meizhou depression belt of eastern China. Garnet is a characteristic mineral in the deposit. Two generations of garnets are detected in the deposit based on their textural characteristics and trace-element contents, and are represented by Fe-enriched andradite. The first generation of garnets (Grt1) have two types of garnets (Grt1-A and Grt1-B). Type A garnets of the first generation (Grt1-A) (Adr80-88) replaced by massive diopside-magnetite assemblage exhibit distinct oscillatory zonings and display patterns of enriched light rare earth elements (LREE) to weak heavy rare earth elements (HREE), with weak negative to positive Eu anomalies, and highest U, ΣREE and Sn contents. Type B garnets of the first generation (Grt1-B) are irregular zones (Adr94-96) coexisting with magnetite, in which Grt1-A is generally dissolved, and have obviously LREE-enriched and HREE-depleted patterns, with weak negative to positive Eu anomalies, and moderate U, ΣREE and Zn contents. Garnets of the second generation (Grt2) (Adr96-99) that replaced massive magnetite together with sphalerite show unzoned patterns, with a flat REE pattern and pronounced negative Eu anomalies as well as contents of lowest U and ΣREE, and highest W. The substitution of REEs in garnets occurs as [X2+]VIII –1[REE3+]VIII +1[Si4+]IV –1[Z3+]IV +1in an Al-enriched environment. Luoyang hydrothermal fluids shifted from reducing conditions with relatively high-U and -ΣREE characteristics to oxidizing conditions with relatively low-U and -ΣREE characteristics. The reduced siderophile elements and increased fO2 in fluid during Grt1-B formation caused magnetite mineralization and reduced Zn contents during Grt2 formation, causing the deposition of sphalerite. All garnets formed from magmatic fluid and were controlled by infiltrative metasomatism in an opened system.
Schizophrenia has been primarily conceptualized as a disorder of high-order cognitive functions with deficits in executive brain regions. Yet due to the increasing reports of early sensory processing deficit, recent models focus more on the developmental effects of impaired sensory process on high-order functions. The present study examined whether this pathological interaction relates to an overarching system-level imbalance, specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks.
Methods
We applied a novel combination of connectome gradient and stepwise connectivity analysis to resting-state fMRI to characterize the sensorimotor-to-transmodal cortical hierarchy organization (96 patients v. 122 controls).
Results
We demonstrated compression of the cortical hierarchy organization in schizophrenia, with a prominent compression from the sensorimotor region and a less prominent compression from the frontal−parietal region, resulting in a diminished separation between sensory and fronto-parietal cognitive systems. Further analyses suggested reduced differentiation related to atypical functional connectome transition from unimodal to transmodal brain areas. Specifically, we found hypo-connectivity within unimodal regions and hyper-connectivity between unimodal regions and fronto-parietal and ventral attention regions along the classical sensation-to-cognition continuum (voxel-level corrected, p < 0.05).
Conclusions
The compression of cortical hierarchy organization represents a novel and integrative system-level substrate underlying the pathological interaction of early sensory and cognitive function in schizophrenia. This abnormal cortical hierarchy organization suggests cascading impairments from the disruption of the somatosensory−motor system and inefficient integration of bottom-up sensory information with attentional demands and executive control processes partially account for high-level cognitive deficits characteristic of schizophrenia.
Microglia, the main immune cell of the central nervous system (CNS), categorized into M1-like phenotype and M2-like phenotype, play important roles in phagocytosis, cell migration, antigen presentation, and cytokine production. As a part of CNS, retinal microglial cells (RMC) play an important role in retinal diseases. Diabetic retinopathy (DR) is one of the most common complications of diabetes. Recent studies have demonstrated that DR is not only a microvascular disease but also retinal neurodegeneration. RMC was regarded as a central role in neurodegeneration and neuroinflammation. Therefore, in this review, we will discuss RMC polarization and its possible regulatory factors in early DR, which will provide new targets and insights for early intervention of DR.
Type III radio bursts are radio emissions associated with solar flares. They are considered to be caused by electron beams travelling from the solar corona to the solar wind. Magnetic reconnection is a possible accelerator of electron beams in the course of solar flares since it causes unstable distribution functions and density inhomogeneities (cavities). The properties of radio emission by electron beams in an inhomogeneous environment are still poorly understood. We capture the nonlinear kinetic plasma processes of the generation of beam-related radio emissions in inhomogeneous plasmas by utilizing fully kinetic particle-in-cell code numerical simulations. Our model takes into account initial electron velocity distribution functions (EVDFs) as they are supposed to be created by magnetic reconnection. We focus our analysis on low-density regions with strong magnetic fields. The assumed EVDFs allow two distinct mechanisms of radio wave emissions: plasma emission due to wave–wave interactions and so-called electron cyclotron maser emission (ECME) due to direct wave–particle interactions. We investigate the effects of density inhomogeneities on the conversion of free energy from the electron beams into the energy of electrostatic and electromagnetic waves via plasma emission and ECME, as well as the frequency shift of electron resonances caused by perpendicular gradients in the beam EVDFs. Our most important finding is that the number of harmonics of Langmuir waves increases due to the presence of density inhomogeneities. The additional harmonics of Langmuir waves are generated by a coalescence of beam-generated Langmuir waves and their harmonics.
Based on a cohort from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), we aimed to evaluate the relationship between sleep duration and the incidence of cognitive impairment among older Chinese adults.
Methods:
We conducted a prospective analysis based on 3692 participants from the CLHLS at baseline (in 2011), and as a 3-year follow-up (till 2014), 531 participants (14.4%) had cognitive impairment, which was defined as a Mini-Mental State Examination score <24. Sleep duration was classified into three groups: short (≤5 hours/day), normal (>5 but <10 hours), and long (≥10 hours/day). A logistic regression model was used to examine the association between baseline sleep duration and cognitive impairment after adjusting for sociodemographic data, living habits, and health conditions.
Results:
Five hundred sixty-two participants (15.2%) were in the short-duration group, and 608 participants (16.5%) were in the long-duration group. After adjusting for multiple potential confounders, compared with normal sleep duration, long sleep duration was associated with the incidence of cognitive impairment (OR = 1.309, 95% CI: 1.019–1.683), especially among men (OR = 1.527, 95% CI: 1.041–2.240) and those having a primary and above education level (OR = 1.559, 95% CI: 1.029–2.361). No significant association was observed between short sleep duration and cognitive impairment (OR = 0.860, 95% CI: 0.646–1.145).
Conclusions:
Excessive sleep may increase the risk of cognitive impairment in older individuals. It may be a suggestive sign of early neurodegeneration and may be a useful clinical tool to identify those at a higher risk of progressing to cognitive impairment.
Supraglacial lakes and rivers dominate the storage and transport of meltwater on the southwest Greenland Ice Sheet (GrIS) surface. Despite functioning as interconnected hydrologic networks, supraglacial lakes and rivers are commonly studied as independent features, resulting in an incomplete understanding of their collective impact on meltwater storage and routing. We use Landsat 8 satellite imagery to assess the seasonal evolution of supraglacial lakes and rivers on the southwest GrIS during the 2015 melt season. Remotely sensed meltwater areas and volumes are compared with surface runoff simulations from three climate models (MERRA-2, MAR 3.6 and RACMO 2.3), and with in situ observations of proglacial discharge in the Watson River. We find: (1) at elevations >1600 m, 21% of supraglacial lakes and 28% of supraglacial rivers drain into moulins, signifying the presence of high-elevation surface-to-bed meltwater connections even during a colder-than-average melt season; (2) while supraglacial lakes dominate instantaneous surface meltwater storage, supraglacial rivers dominate total surface meltwater area and discharge; (3) the combined surface area of supraglacial lakes and rivers is strongly correlated with modeled surface runoff; and (4) of the three models examined here, MERRA-2 runoff yields the highest overall correlation with observed proglacial discharge in the Watson River.
Neuroimaging characteristics have demonstrated disrupted functional organization in schizophrenia (SZ), involving large-scale networks within grey matter (GM). However, previous studies have ignored the role of white matter (WM) in supporting brain function.
Methods
Using resting-state functional MRI and graph theoretical approaches, we investigated global topological disruptions of large-scale WM and GM networks in 93 SZ patients and 122 controls. Six global properties [clustering coefficient (Cp), shortest path length (Lp), local efficiency (Eloc), small-worldness (σ), hierarchy (β) and synchronization (S) and three nodal metrics [nodal degree (Knodal), nodal efficiency (Enodal) and nodal betweenness (Bnodal)] were utilized to quantify the topological organization in both WM and GM networks.
Results
At the network level, both WM and GM networks exhibited reductions in Eloc, Cp and S in SZ. The SZ group showed reduced σ and β only for the WM network. Furthermore, the Cp, Eloc and S of the WM network were negatively correlated with negative symptoms in SZ. At the nodal level, the SZ showed nodal disturbances in the corpus callosum, optic radiation, posterior corona radiata and tempo-occipital WM tracts. For GM, the SZ manifested increased nodal centralities in frontoparietal regions and decreased nodal centralities in temporal regions.
Conclusions
These findings provide the first evidence for abnormal global topological properties in SZ from the perspective of a substantial whole brain, including GM and WM. Nodal centralities enhance GM areas, along with a reduction in adjacent WM, suggest that WM functional alterations may be compensated for adjacent GM impairments in SZ.