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Inconsistent findings persist across resting-state functional imaging studies of regional brain alterations in postpartum depression (PPD), while connections to transcriptional profiles and neurotransmitter systems remain largely uncharacterized.
Methods
We performed a whole-brain voxel-wise meta-analysis of resting-state functional imaging studies comparing PPD patients and healthy controls using SDM-PSI software. JuSpace toolbox analyzed atlas-based nuclear imaging-derived neurotransmitter maps, and transcriptional data were sourced from the Allen Human Brain Atlas.
Results
Our systematic review identified 12 functional imaging studies (475 PPD patients, 504 controls). Patients with PPD displayed increased resting-state functional activity in the left inferior occipital gyrus and left precuneus as well as decreased resting-state functional activity in the right amygdala and left precentral gyrus. These functional alterations spatially overlapped with serotonergic, dopaminergic, and VAChT systems. Transcriptional analysis revealed PPD-related gene enrichments in ion channel function (transmembrane transport, gated/passive channels) and channel complexes.
Conclusions
The meta-analysis revealed functional alterations within the DMN, limbic, and primary sensorimotor systems in PPD patients. These changes were linked to neurotransmitter alterations and genetic modulations underlying brain dysfunction. Collectively, these findings advance mechanistic understanding of PPD pathophysiology.
Proton–boron (${\mathrm{p}}^{11}\mathrm{B}$) fusion provides a unique pathway for generating energetic $\alpha$ particles with a low associated neutron background. In this work, we investigate, through particle-in-cell Monte Carlo (PIC-MC) simulations, an enhanced ${\mathrm{p}}^{11}\mathrm{B}$ fusion and $\alpha$ particle production in laser-irradiated nanowire arrays (NWAs). A Monte Carlo ${\mathrm{p}}^{11}\mathrm{B}$ fusion module is first implemented within the EPOCH framework, which helps to reliably simulate the ${\mathrm{p}}^{11}\mathrm{B}$ fusion plasma dynamics. Benchmark tests on the $\alpha$ particle generation in ${\mathrm{p}}^{11}\mathrm{B}$ fusion reactions are performed. The results agree well with both the available experimental and theoretical data, thus validating the implemented ${\mathrm{p}}^{11}\mathrm{B}$ fusion module. This development is then used to study the ${\mathrm{p}}^{11}\mathrm{B}$ fusion plasma dynamics and the resulting production of $\alpha$ particles in the NWA targets composed of octadecaborane, in which Bayesian optimization is performed to search for an optimal laser intensity and NWA configuration. Two-dimensional PIC-MC simulations demonstrate that the NWA targets can produce a flux of energetic $\alpha$ particles approximately two orders of magnitude greater than that of a planar target. This enhancement is mainly attributed to an efficient ion acceleration by sheath fields. It is demonstrated that the proposed optimization framework represents a reliable and efficient tool for studying laser-driven ${\mathrm{p}}^{11}\mathrm{B}$ fusion plasma physics, while providing valuable insights and practical guidance for optimizing NWA targets toward higher reaction yields.
While the late Llandovery brachiopod faunas of South China are well documented, they are known almost exclusively from shallow-water settings. Here, we present a detailed study of a brachiopod fauna from the Ningqiang Formation (early to middle Telychian) at the Bifengguan section in Sichuan Province, South China. Quantitative analyses, including non-metric multidimensional scaling (NMDS) and network analysis, reveal three successive brachiopod associations. Significantly, the basal Aegiria–Epitomyonia association was characterized by the abundance of the deep-water indicator Epitomyonia. This represents the first definitive record of a deep-water (BA4) community within the Telychian Xiushan Fauna, which was previously thought to be restricted to shallower environments. This basal association is succeeded by the Aegiria–Megaspinochonetes and Fardenia–Striispirifer associations, and this complete succession indicates a shallowing-upward environmental trend from a BA4 to an upper BA3 setting. We interpret this shallowing trend as a response to regional uplift. The initial existence of this deep-water association was likely facilitated by the unique paleogeographical position of the locality, which likely provided a stable habitat for this deep-water community. This study expands the known ecological range of the Xiushan Fauna and underscores the critical role of local paleogeography in shaping benthic community structures during the early Silurian.
Structural brain alterations in bipolar disorder (BD) have been widely reported, yet the hierarchical organization of cortical morphometric networks and their molecular and cognitive underpinnings remain unclear.
Methods
We applied the morphometric inverse divergence (MIND) network approach to structural MRI data from 49 BD patients and 119 healthy controls. Principal MIND gradients were derived using diffusion map embedding, followed by multiscale analyses linking gradient alterations to neurotransmitter systems, cognitive-behavioral domains, and transcriptomic profiles from the Allen Human Brain Atlas. Validation was performed in three independent, cross-scanner, cross-race, and cross-age validation datasets.
Results
Bipolar disorder patients showed significant principal gradient alterations in the left rostral middle frontal and lateral occipital cortices, with network-level decreases in the ventral attention and motor networks and increases in frontoparietal and visual networks. Gradient alterations spatially correlated with acetylcholine (VAChT) and GABA (GABAA/BZ) systems, and were associated with cognitive processes involving executive control and visual attention. Transcriptomic analyses identified gene sets enriched for BD-related GWAS loci, expressed predominantly in excitatory and inhibitory neurons, astrocytes, and oligodendrocytes, with preferential enrichment in cortical layers III-IV and developmental windows spanning early fetal to young adulthood.
Conclusions
These findings reveal disrupted hierarchical cortical organization in BD and link macroscale morphometric alterations to specific neurotransmitter systems and transcriptional architectures. The MIND gradient emerges as a potential biomarker bridging structural disruptions with molecular and cognitive mechanisms in BD.
To investigate the characteristics of a turbulent boundary layer (TBL) over the curved edge of the bow of submarine technology program office (SUBOFF) model, wall-resolved large-eddy simulation is conducted at a Reynolds number of $\mathop {\textit{Re}}\nolimits _L = 1.1 \times {10^6}$ based on the model length and free-stream velocity. Instead of using a trip wire at the bow surface, turbulent inflow is added to the simulation to induce boundary layer transition. The effects of geometric curvature and inflow turbulence intensity (ITI) are examined. With a low ITI level, natural transition takes place at the rear end of the straight section. With higher ITI levels, turbulence emerges immediately and evolves gradually, following a strong favourable-pressure-gradient (FPG) region near the forehead, which is significantly influenced by the large streamwise curvature. Within the FPG region, the root mean square of the wall pressure fluctuation (WPF) decreases rapidly, with the frequency spectra of WPF exhibiting good scalability with outer variables. Moreover, higher turbulence intensity levels lead to larger skin friction, which is related to the development of the TBL. To elucidate the generation mechanism of skin friction, the dynamic decomposition is derived in the curvilinear coordinate system. The mean convection and streamwise pressure gradient make the largest contributions to the local skin friction. Furthermore, an analysis of the energy transfer process based on the Reynolds stress transport equations in the curvilinear coordinate system is presented, highlighting the significant impact of geometric effects, particularly on the production term.
This study explores interfacial waves in a three-layer fluid system, focusing on the coupling effects between the two interfaces. These effects include resonance induced by inertial coupling and damping caused by viscous coupling. A linear theoretical framework is developed to describe the coupled wave motion and evaluate the impact of interfacial coupling under viscous damping. Additionally, a semi-analytical model is introduced to accurately capture resonance frequency shifts and phase differences due to viscosity. The spiral structure of interfacial waves predicted by the models is confirmed experimentally using the background oriented Schlieren (BOS) method. Further, the model is validated by excellent agreement between theoretical predictions and ultrasonic measurements of wave amplitudes and phase differences. Finally, the study examines mechanical coupling and energy transfer between interfaces under external forcing, elucidating the formation of spiral waves. The accurate treatment of viscous boundary conditions by the semi-analytical model also enables its extension to multilayer fluid systems.
The Chinese pangolin Manis pentadactyla is categorized as Critically Endangered on the IUCN Red List, but the development of effective conservation strategies is hindered by a lack of data on its distribution range and population dynamics. In addition, standardized survey and analysis methods are required to facilitate the sharing of results and maximize conservation effectiveness. To fill these knowledge and methodological gaps, we investigated the occurrence of pangolin burrows in the subtropical forest ecosystem of Fujian, China. We surveyed a total of 70 transects across five land-cover types within the Fujian Junzifeng National Nature Reserve and detected 87 burrows. The majority of burrows (87%) were located in mixed conifer and broadleaf forests. We used six environmental variables in a generalized linear model to examine the relationship between the occurrence of burrows and environmental factors. The average model results from the best model set showed that the distribution of burrows was significantly influenced by forest type. For effective pangolin conservation, we recommend that local conservation authorities prioritize the protection of mixed conifer and broadleaf forests. Our findings support the local conservation of the Chinese pangolin and the standardization of surveys and conservation efforts across the species’ range.
Parental psychopathology is a known risk factor for child autistic-like traits. However, symptom-level associations and underlying mechanisms are poorly understood.
Methods
We utilized network analyses and cross-lagged panel models to investigate the specific parental psychopathology related to child autistic-like traits among 8,571 adolescents (mean age, 9.5 years at baseline), using baseline and 2-year follow-up data from the Adolescent Brain Cognitive Development study. Parental psychopathology was measured by the Adult Self Report, and child autistic-like traits were measured by three methods: the Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5 autism spectrum disorder (ASD) subscale, the Child Behavior Checklist ASD subscale, and the Social Responsiveness Scale. We also examined the mediating roles of family conflict and children’s functional brain connectivity at baseline.
Results
Parental attention-deficit/hyperactivity problems were central symptoms and had a direct and the strongest link with child autistic-like traits in network models using baseline data. In longitudinal analyses, parental attention-deficit/hyperactivity problems at baseline were the only significant symptoms associated with child autistic-like traits at 2-year follow-up (β = 0.014, 95% confidence interval [0.010, 0.018], FDR q = 0.005), even accounting for children’s comorbid behavioral problems. The observed association was significantly mediated by family conflict (proportion mediated = 11.5%, p for indirect effect <0.001) and functional connectivity between the default mode and dorsal attention networks (proportion mediated = 0.7%, p for indirect effect = 0.047).
Conclusions
Parental attention-deficit/hyperactivity problems were associated with elevated autistic-like traits in offspring during adolescence.
This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.
In the digital era, short videos have become a significant form of digital copyright, yet the debate over whether stronger copyright protection enhances their creation continues. To contribute to this discourse, we conducted an analysis based on a representative sample of short videos on a prominent Chinese short video platform, Douyin. Capitalizing on an external regulatory intervention, specifically the Campaign against Online Infringement and Piracy (COIP) implemented by the Chinese government, we employed the difference-in-differences (DID) method to assess the impact of reinforced copyright protection on the originality of short videos. Our findings reveal that strengthened copyright protection leads to a significant increase in the originality of short videos. Further research on creator heterogeneity shows that influencers exhibit a significantly more positive response to strengthened copyright protection than amateur creators. Finally, we present evidence explaining how external regulation works by enhancing intra-platform regulation. These results have rich implications for intellectual property protection, digital innovation management, and platform regulation.
The expanding application of advanced analytics in insurance has generated numerous opportunities, such as more accurate predictive modeling powered by machine learning and artificial intelligence (AI) methods, the utilization of novel and unstructured datasets, and the automation of key operations. Significant advances in these areas are being made through novel applications and adaptations of predictive modeling techniques for insurance purposes, while, concurrently, rapid advances in machine learning methods are being made outside of the insurance sector. However, these innovations also bring substantial challenges, particularly around the transparency, explanation, and fairness of complex algorithmic models and the economic and societal impacts of their adoption in decision-making. As insurance is a highly regulated industry, models may be required by regulators to be explainable, in order to enable analysis of the basis for decision making. Due to the societal importance of insurance, significant attention is being paid to ensuring that insurance models do not discriminate unfairly. In this special issue, we feature papers that explore key issues in insurance analytics, focusing on prediction, explainability, and fairness.
In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
To investigate the associations between dietary patterns and biological ageing, identify the most recommended dietary pattern for ageing and explore the potential mediating role of gut microbiota in less-developed ethnic minority regions (LEMRs). This prospective cohort study included 8288 participants aged 30–79 years from the China Multi-Ethnic Cohort study. Anthropometric measurements and clinical biomarkers were utilised to construct biological age based on Klemera and Doubal’s method (KDM-BA) and KDM-BA acceleration (KDM-AA). Dietary information was obtained through the baseline FFQ. Six dietary patterns were constructed: plant-based diet index, healthful plant-based diet index, unhealthful plant-based diet index, healthy diet score, Dietary Approaches to Stop Hypertension (DASH), and alternative Mediterranean diets. Follow-up adjusted for baseline analysis assessed the associations between dietary patterns and KDM-AA. Additionally, quantile G-computation identified significant beneficial and harmful food groups. In the subsample of 764 participants, we used causal mediation model to explore the mediating role of gut microbiota in these associations. The results showed that all dietary patterns were associated with KDM-AA, with DASH exhibiting the strongest negative association (β = −0·91, 95 % CI (–1·19, −0·63)). The component analyses revealed that beneficial food groups primarily included tea and soy products, whereas harmful groups mainly comprised salt and processed vegetables. In mediation analysis, the Synergistetes and Pyramidobacter possibly mediated the negative associations between plant-based diets and KDM-AA (5·61–9·19 %). Overall, healthy dietary patterns, especially DASH, are negatively associated with biological ageing in LEMRs, indicating that Synergistetes and Pyramidobacter may be potential mediators. Developing appropriate strategies may promote healthy ageing in LEMRs.
We investigate the Faraday instabilities of a three-layer fluid system in a cylindrical container containing low-viscosity liquid metal, sodium hydroxide solution and air by establishing the Mathieu equations with considering the viscous model derived by Labrador et al. (J. Phys.: Conf. Ser., vol. 2090, 2021, 012088). The Floquet analysis, asymptotic analysis, direct numerical simulation and experimental method are adopted in the present study. We obtain the dispersion relations and critical oscillation amplitudes of zigzag and varicose modes from the analysis of the Mathieu equations, which agree well with the experimental result. Furthermore, considering the coupling strength of two interfaces, besides zigzag and varicose modes, we find a beating instability mode that contains two primary frequencies, with its average frequency equalling half of the external excitation frequency in the strongly coupled system. In the weakly coupled system, the $A$-interface instability, $B$-interface instability and $A$&$B$-interface instability are defined. Finally, we obtain a critical wavenumber $k_c$ that can determine the transition from zigzag or varicose modes to the corresponding $A$-interface or $B$-interface instability.
The association between obesity and depression may partly depend on the contextual metabolic health. The effect of change in metabolic health status over time on subsequent depression risk remains unclear. We aimed to assess the prospective association between metabolic health and its change over time and the risk of depression across body mass index (BMI) categories.
Methods
Based on a nationally representative cohort, we included participants enrolled at the wave 2 (2004–2005) of the English Longitudinal Study of Ageing and with follow-up for depression at wave 8 (2016–2017). Participants were cross-classified by BMI categories and metabolic health (defined by the absence of hypertension, diabetes, and hypercholesterolemia) at baseline or its change over time (during waves 3–6). Logistic regression model was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of depression at follow-up stratified by BMI category and metabolic health status with adjustment for potential confounders.
Results
The risk of depression was increased for participants with metabolically healthy obesity compared with healthy nonobese participants, and the risk was highest for those with metabolically unhealthy obesity (OR 1.62, 95% CI 1.18–2.20). Particularly hypertension and diabetes contribute most to the increased risk. The majority of metabolically healthy participants converted to unhealthy metabolic phenotype (50.1% of those with obesity over 8 years), which was associated with an increased risk of depression. Participants who maintained metabolically healthy obesity were still at higher risk (1.99, 1.33–2.72), with the highest risk observed for those with stable unhealthy metabolic phenotypes.
Conclusions
Obesity remains a risk factor for depression, independent of whether other metabolic risk factors are present or whether participants convert to unhealthy metabolic phenotypes over time. Long-term maintenance of metabolic health and healthy body weight may be beneficial for the population mental well-being.
COVID-19 lockdowns increased the risk of mental health problems, especially for children with autism spectrum disorder (ASD). However, despite its importance, little is known about the protective factors for ASD children during the lockdowns.
Methods
Based on the Shanghai Autism Early Developmental Cohort, 188 ASD children with two visits before and after the strict Omicron lockdown were included; 85 children were lockdown-free, while 52 and 51 children were under the longer and the shorter durations of strict lockdown, respectively. We tested the association of the lockdown group with the clinical improvement and also the modulation effects of parent/family-related factors on this association by linear regression/mixed-effect models. Within the social brain structures, we examined the voxel-wise interaction between the grey matter volume and the identified modulation effects.
Results
Compared with the lockdown-free group, the ASD children experienced the longer duration of strict lockdown had less clinical improvement (β = 0.49, 95% confidence interval (CI) [0.19–0.79], p = 0.001) and this difference was greatest for social cognition (2.62 [0.94–4.30], p = 0.002). We found that this association was modulated by parental agreeableness in a protective way (−0.11 [−0.17 to −0.05], p = 0.002). This protective effect was enhanced in the ASD children with larger grey matter volumes in the brain's mentalizing network, including the temporal pole, the medial superior frontal gyrus, and the superior temporal gyrus.
Conclusions
This longitudinal neuroimaging cohort study identified that the parental agreeableness interacting with the ASD children's social brain development reduced the negative impact on clinical symptoms during the strict lockdown.
In this paper, we propose a numerical model to simulate gas–liquid–solid interaction problems, coupling the lattice Boltzmann method and discrete element method (LBM–DEM). A cascaded LBM is used to simulate the liquid–gas flow field using a pseudopotential interaction model for describing the liquid–gas multiphase behaviour. A classical DEM resorting to fictitious overlaps between the particles is used to simulate the multiple-solid-particle system. A multiphase fluid–solid two-way coupling algorithm between LBM and DEM is constructed. The model is validated by four benchmarks: (i) single disc sedimentation, (ii) single floating particle on a liquid–gas interface, (iii) sinking of a horizontal cylinder and (iv) self-assembly of three particles on a liquid–gas interface. Our simulations agree well with the numerical results reported in the literature. Our proposed model is further applied to simulate droplet impact on deformable granular porous media at pore scale. The dynamic droplet spreading process, the deformation of the porous media (composed of up to 1277 solid particles) as well as the invasion of the liquid into the pores are well captured, within a wide range of impact Weber number. The droplet spreading dynamics on particles is analysed based on the energy budget, which reveals mechanisms at play, showing the evolution of particle energy, surface energy and viscous dissipation energy. A scaling relation based on the impact Weber number is proposed to describe the maximum spreading ratio.
The association between time-restricted eating (TRE) and the risk of non-alcoholic fatty liver disease (NAFLD) is less studied. Moreover, whether the association is independent of physical exercise or diet quality or quantity is uncertain. In this nationwide cross-sectional study of 3813 participants, the timing of food intakes was recorded by 24-h recalls; NAFLD was defined through vibration-controlled transient elastography in the absence of other causes of chronic liver disease. OR and 95 % CI were estimated using logistic regression. Participants with daily eating window of ≤ 8 h had lower odds of NAFLD (OR = 0·70, 95 % CI: 0·52, 0·93), compared with those with ≥ 10 h window. Early (05.00–15.00) and late TRE (11.00–21.00) showed inverse associations with NAFLD prevalence without statistical heterogeneity (Pheterogeneity = 0·649) with OR of 0·73 (95 % CI: 0·36, 1·47) and 0·61 (95 % CI: 0·44, 0·84), respectively. Such inverse association seemed stronger in participants with lower energy intake (OR = 0·58, 95 % CI: 0·38, 0·89, Pinteraction = 0·020). There are no statistical differences in the TRE-NAFLD associations according to physical activity (Pinteraction = 0·390) or diet quality (Pinteraction = 0·110). TRE might be associated with lower likelihood of NAFLD. Such inverse association is independent of physical activity and diet quality and appears stronger in individuals consuming lower energy. Given the potential misclassification of TRE based on one- or two-day recall in the analysis, epidemiological studies with validated methods for measuring the habitual timing of dietary intake are warranted.
Coastal eutrophication and hypoxia remain a persistent environmental crisis despite the great efforts to reduce nutrient loading and mitigate associated environmental damages. Symptoms of this crisis have appeared to spread rapidly, reaching developing countries in Asia with emergences in Southern America and Africa. The pace of changes and the underlying drivers remain not so clear. To address the gap, we review the up-to-date status and mechanisms of eutrophication and hypoxia in global coastal oceans, upon which we examine the trajectories of changes over the 40 years or longer in six model coastal systems with varying socio-economic development statuses and different levels and histories of eutrophication. Although these coastal systems share common features of eutrophication, site-specific characteristics are also substantial, depending on the regional environmental setting and level of social-economic development along with policy implementation and management. Nevertheless, ecosystem recovery generally needs greater reduction in pressures compared to that initiated degradation and becomes less feasible to achieve past norms with a longer time anthropogenic pressures on the ecosystems. While the qualitative causality between drivers and consequences is well established, quantitative attribution of these drivers to eutrophication and hypoxia remains difficult especially when we consider the social economic drivers because the changes in coastal ecosystems are subject to multiple influences and the cause–effect relationship is often non-linear. Such relationships are further complicated by climate changes that have been accelerating over the past few decades. The knowledge gaps that limit our quantitative and mechanistic understanding of the human-coastal ocean nexus are identified, which is essential for science-based policy making. Recognizing lessons from past management practices, we advocate for a better, more efficient indexing system of coastal eutrophication and an advanced regional earth system modeling framework with optimal modules of human dimensions to facilitate the development and evaluation of effective policy and restoration actions.
Customer churn, which insurance companies use to describe the non-renewal of existing customers, is a widespread and expensive problem in general insurance, particularly because contracts are usually short-term and are renewed periodically. Traditionally, customer churn analyses have employed models which utilise only a binary outcome (churn or not churn) in one period. However, real business relationships are multi-period, and policyholders may reside and transition between a wider range of states beyond that of the simply churn/not churn throughout this relationship. To better encapsulate the richness of policyholder behaviours through time, we propose multi-state customer churn analysis, which aims to model behaviour over a larger number of states (defined by different combinations of insurance coverage taken) and across multiple periods (thereby making use of readily available longitudinal data). Using multinomial logistic regression (MLR) with a second-order Markov assumption, we demonstrate how multi-state customer churn analysis offers deeper insights into how a policyholder’s transition history is associated with their decision making, whether that be to retain the current set of policies, churn, or add/drop a coverage. Applying this model to commercial insurance data from the Wisconsin Local Government Property Insurance Fund, we illustrate how transition probabilities between states are affected by differing sets of explanatory variables and that a multi-state analysis can potentially offer stronger predictive performance and more accurate calculations of customer lifetime value (say), compared to the traditional customer churn analysis techniques.