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This work proposes a data-driven explicit algebraic stress-based detached-eddy simulation (DES) method. Despite the widespread use of data-driven methods in model development for both Reynolds-averaged Navier–Stokes (RANS) and large-eddy simulations (LES), their applications to DES remain limited. The challenge mainly lies in the absence of modelled stress data, the requirement for proper length scales in RANS and LES branches, and the maintenance of a reasonable switching behaviour. The data-driven DES method is constructed based on the algebraic stress equation. The control of RANS/LES switching is achieved through the eddy viscosity in the linear part of the modelled stress, under the $\ell ^2-\omega$ DES framework. Three model coefficients associated with the pressure–strain terms and the LES length scale are represented by a neural network as functions of scalar invariants of velocity gradient. The neural network is trained using velocity data with the ensemble Kalman method, thereby circumventing the requirement for modelled stress data. Moreover, the baseline coefficient values are incorporated as additional reference data to ensure reasonable switching behaviour. The proposed approach is evaluated on two challenging turbulent flows, i.e. the secondary flow in a square duct and the separated flow over a bump. The trained model achieves significant improvements in predicting mean flow statistics compared with the baseline model. This is attributed to improved predictions of the modelled stress. The trained model also exhibits reasonable switching behaviour, enlarging the LES region to resolve more turbulent structures. Furthermore, the model shows satisfactory generalization capabilities for both cases in similar flow configurations.
In this paper, we numerically investigate the orbit dynamics of three-dimensional symmetric Janus drops in shear flow using an improved ternary-fluids phase field method, focusing on how drop deformation and initial orientation affect the orbit drift of two configurations of Janus drops: dumbbell-shaped and near-spherical. We find that the motion of dumbbell-shaped drops eventually evolves into tumbling, while near-spherical drops attain stable spinning. We attribute this bifurcation in orbit drift to contrasting deformation dynamics and shape-dependent hydrodynamics of the two configurations. Specifically, the drift bifurcation is closely related to the aspect ratio of Janus drops at equilibrium, giving rise to two distinct mechanisms: (1) coupling between outer interface deformation and the surrounding flow field; and (2) interplay between inner interface deformation and vortices enclosed within the drop. In addition, we observe that for the dumbbell-shaped Janus drops with different aspect ratios, their tumbling dynamics resembles ellipsoids in shear flow. Moreover, the trajectories of the dumbbell-shaped Janus drops during orbit drift collapse onto a universal curve, independent of their initial orientations, and significant deformation and inertia accelerate the orbit transition. To quantitatively evaluate the effect of drop deformation on the orbit drift of the dumbbell-shaped Janus drops, we propose an effective aspect ratio model based on the drop shapes at equilibrium and at the maximum elongation. By incorporating the effective aspect ratio into Jeffery’s theory for solid particles, we accurately predict the rotation period and angular velocity of Janus drops in the tumbling regime and during the orbit drift, especially for drops with linear deformation. Moreover, the orbit parameter $C$ is found to vary exponentially with time for drops with linear deformation, while the time variation of $C$ transits from one exponential function to another for drops with nonlinear deformation.
As GLP-1 receptor agonists (GLP-1 RAs) are increasingly used worldwide, concerns about their association with mood disorders have grown. Yet real-world observational studies have produced conflicting findings. This study aims to fully examine the link between GLP-1 RAs and emotional/behavioral outcomes.
Methods
Disproportionality analysis of GLP-1 RA adverse events was conducted using FAERS data. Mendelian randomization (MR) employed GLP1R cis-eQTLs as instrumental variables to assess links with mood/behavior-related disorders. Summary-data MR (SMR) was then performed using GLP1R cis-eQTL data.
Results
275,718 adverse events (AEs) associated with GLP-1 RAs were retrieved and analyzed. A mild signal for suicide-related AEs was observed only in the obesity indication subgroup (ROR:1.65, 95% CI: 1.28–2.12). Genetic evidence showed that GLP-1 RAs were likely associated with reduced risks of anxiety, depression, emotional lability, bipolar disorder, and suicide. Mediational analysis indicated that weight loss partially mediated the causal effects of GLP-1 RAs on depression and emotional lability, accounting for 18.28% (95% CI: 9.46–27.10%, P = 0.038) and 7.65% (95% CI: 5.66–9.64%, P < 0.001) of the total effects, respectively. SMR analysis showed that genetically predicted GLP1R expression was negatively associated with anxiety (OR: 0.79, 95% CI: 0.64–0.98, P = 0.031), with no significant associations for other emotional or behavioral outcomes.
Conclusions
Both observational and MR analyses showed that patients treated with GLP-1 RAs may have no increased risk of emotional and behavioral disorders. Instead, genetic proxy activation of GLP-1 RAs may reduce the risk of anxiety, depression, and emotional lability.
Major depressive disorder (MDD) patients exhibit a mood-congruent emotional processing bias within the amygdala toward negative facial stimuli at both unconscious and conscious levels. Therefore, our study aimed to investigate the temporal and spatial dynamics of amygdala along with its interactions with the whole brain during implicit and explicit conditions in MDD.
Methods
Thirty MDD patients and 26 healthy controls (HCs) underwent magnetoencephalography (MEG) recordings and performed implicit and explicit emotional face recognition tasks with happy, sad, and neutral facial expressions. Using the amygdala as a seed region, time frequency representations (TFR) and functional connectivity (FC) were calculated. Pearson correlation analyses measured the relationship between TFR and FC values with clinical symptoms.
Results
During implicit processing, MDD patients exhibited left amygdala activation in the gamma power (60–70 Hz) before 250 ms in response to sad facial stimuli compared to HCs. In the implicit mode, there were increased FC between the right amygdala and several brain regions in the occipitoparietal lobes, as well as higher FC between the left amygdala and putamen in MDD patients. Additionally, the right amygdala was positively correlated with the severity of depression and anxiety during implicit processing.
Conclusions
MDD patients had lateralized amygdala activation in response to sad facial expressions during unconscious emotional recognition of facial stimuli. Our study provided valuable insights into the spatiotemporal dynamics of facial emotional recognition associated with depressive and anxiety-related cognitive bias during implicit and explicit processing.
To investigate multiple effects of the interaction between V. cholerae and phage on cholera transmission, we propose a degenerate reaction-diffusion model with different dispersal rates, which incorporates a short-lived hyperinfectious (HI vibrios) state of V. cholerae and lower-infectious (LI vibrios) state of V. cholerae. Our main purpose is to investigate the existence and stability analysis of multi-class boundary steady states, which is much more complicated and challenging than the case when the boundary steady state is unique. In a spatially heterogeneous case, the basic reproduction number $\mathscr{R}_{0}$ is defined as the spectral radius of the sum of two linear operators associated with HI vibrios infection and LI vibrios infection. If $\mathscr{R}_{0}\leq 1$, the disease-free steady state is globally asymptotically stable. If $\mathscr{R}_{0}\gt 1$, the uniform persistence of phage-free model, as well as the existence of the phage-free steady state, are established. In a spatially homogeneous case, when $\ \;\widetilde{\!\!\!\mathscr{R}}_{0}\gt 1$, the global asymptotic stability of phage-free steady state and the uniform persistence of the phage-present model are discussed under some additional conditions. The mathematical approach here has wide applications in degenerate Partial Differential Equations.
In this paper we propose a novel control strategy for modulating nonlinear flapping and symmetry-breaking (S-B) bifurcations of a piezoelectric metamaterial beam behind a circular cylinder subjected to viscous flow. The beam incorporates distributed piezoelectric meta-cells connected via unidirectional circuits to enable self-sensing and adaptive control. A strongly coupled nonlinear fluid-structure-electro-control model within an arbitrary Lagrangian–Eulerian framework is developed for predicting the flapping dynamics of the large deformable piezoelectric metamaterial beam. The system exhibits multiple flow-induced modes, including limit-cycle oscillations, subharmonic responses and S-B deflections. These dynamic regimes arise from nonlinear bifurcations of the system, namely the period-doubling and spontaneous S-B bifurcations. Flapping control and wake topology transition of the system is achieved by suppressing the periodic-doubling bifurcation based on the vibration rebound effect through a self-sensing and adaptive-actuation mechanism of the beam. Floquet stability analysis confirms the effectiveness of control in delaying instability onset and suppressing chaotic transitions. Symmetry modulation of the beam is achieved via the localised perturbations induced from the piezoelectric meta-cells, which reshape the stability of the system. The transition from S-B mode to symmetry-recovery mode reflects a shift from a flow-separation-dominated to vibration-dominated vortex shedding pattern. This symmetry transition reorganises the energy exchange pathways between the flow and the beam. Quantitative analyses of the wake recovery and the energy harvesting efficiency confirm enhanced flow energy conversion under control. These results establish a framework for bifurcation control of slender structures in viscous flow, providing potential applications for underwater energy harvesting and flexible propulsion in unsteady environments.
This study aimed to explore clinical characteristics and treatment efficacy in patients with posterior canal benign paroxysmal positional vertigo and different sleep qualities.
Methods
Patients with posterior canal benign paroxysmal positional vertigo were divided into high and low sleep quality groups based on Pittsburgh Sleep Quality Index scores.
Results
No significant baseline differences existed between low (n = 53) and high (n = 39) sleep quality groups. However, the proportion of cupulolithiasis was higher in the low sleep quality group (60.38 per cent vs. 35.90 per cent; p < 0.05). Additionally, the low sleep quality group had a longer median duration of upbeat nystagmus during the Dix-Hallpike test (63.50 seconds vs. 26.80 seconds; p < 0.05) and a lower cured rate in initial repositioning (9.43 per cent vs. 56.41 per cent) compared to high sleep quality group. Repositioning therapy significantly improved depressive and anxiety symptoms in all patients with posterior canal benign paroxysmal positional vertigo, with a more pronounced improvement in depressive symptoms in the low sleep quality group.
Conclusion
Poor sleep quality is associated with higher cupulolithiasis prevalence and treatment resistance, with residual symptoms mainly affecting social functioning.
Social determinants of health (SDHs) exert a significant influence on various health outcomes and disparities. This study aimed to explore the associations between combined SDHs and mortality, as well as adverse health outcomes among adults with depression.
Methods
The research included 48,897 participants with depression from the UK Biobank and 7,771 from the US National Health and Nutrition Examination Survey (NHANES). By calculating combined SDH scores based on 14 SDHs in the UK Biobank and 9 in the US NHANES, participants were categorized into favourable, medium and unfavourable SDH groups through tertiles. Cox regression models were used to evaluate the impact of combined SDHs on mortality (all-cause, cardiovascular disease [CVD] and cancer) in both cohorts, as well as incidences of CVD, cancer and dementia in the UK Biobank.
Results
In the fully adjusted models, compared to the favourable SDH group, the hazard ratios for all-cause mortality were 1.81 (95% CI: 1.60–2.04) in the unfavourable SDH group in the UK Biobank cohort; 1.61 (95% CI: 1.31–1.98) in the medium SDH group and 2.19 (95% CI: 1.78–2.68) in the unfavourable SDH group in the US NHANES cohort. Moreover, higher levels of unfavourable SDHs were associated with increased mortality risk from CVD and cancer. Regarding disease incidence, they were significantly linked to higher incidences of CVD and dementia but not cancer in the UK Biobank.
Conclusions
Combined unfavourable SDHs were associated with elevated risks of mortality and adverse health outcomes among adults with depression, which suggested that assessing the combined impact of SDHs could serve as a key strategy in preventing and managing depression, ultimately helping to reduce the burden of disease.
Some cadres receive promotions, whereas others do not. This study explores the Chinese Communist Party’s (CCP) personnel control over the central state-owned enterprise (SOE) leaders from the Hu era to the Xi era. An analysis of the résumés and careers of SOE leaders reveals that the CCP has established a dual-track system to manage enterprises with different functions. This system employs two types of incentives: promotion incentives for leaders of eldest-son enterprises associated with national security, and salary incentives for leaders of other enterprises. Through the dual-track system, the CCP aims to influence the career trajectories of SOE leaders and address conflicts of interest in the principal-agent relationship. This study also investigates the individual characteristics of SOE leaders, including their political qualifications, professional qualifications and ages. The results indicate a tendency towards specialization and institutionalization in central-enterprise leaders, even during the Xi era.
The incorporation of trace metals into land snail shells may record the ambient environmental conditions, yet this potential remains largely unexplored. In this study, we analyzed modern snail shells (Cathaica sp.) collected from 16 sites across the Chinese Loess Plateau to investigate their trace metal compositions. Our results show that both the Sr/Ca and Ba/Ca ratios exhibit minimal intra-shell variability and small inter-shell variability at individual sites. A significant positive correlation is observed between the shell Sr/Ca and Ba/Ca ratios across the plateau, with higher values being recorded in the northwestern sites where less monsoonal rainfall is received. We propose that shell Sr/Ca and Ba/Ca ratios, which record the composition of soil solution, may be controlled by the Rayleigh distillation in response to prior calcite precipitation. Higher rainfall amounts may lead to a lower degree of Rayleigh distillation and thus lower shell Sr/Ca and Ba/Ca ratios. This is supported by the distinct negative correlation between summer precipitation and shell Sr/Ca and Ba/Ca ratios, enabling us to reconstruct summer precipitation amounts using the Sr/Ca and Ba/Ca ratios of Cathaica sp. shells. The potential application of these novel proxies may also be promising for other terrestrial mollusks living in the loess deposits globally.
Cavitation bubble pulsation and liquid jet loads are the main causes of hydraulic machinery erosion. Methods to weaken the load influences have always been hot topics of related research. In this work, a method of attaching a viscous layer to a rigid wall is investigated in order to reduce cavitation pulsations and liquid jet loads, using both numerical simulations and experiments. A multiphase flow model incorporating viscous effects has been developed using the Eulerian finite element method (EFEM), and experimental methods of a laser-induced bubble near the viscous layer attached on a rigid wall have been carefully designed. The effects of the initial bubble–wall distance, the thickness of the viscous layer, and the viscosity on bubble pulsation, migration and wall pressure load are investigated. The results show that the bubble migration distance, the normalised thickness of the oil layer and the wall load generally decrease with the initial bubble–wall distance or the oil-layer parameters. Quantitative analysis reveals that when the initial bubble–wall distance remains unchanged, there exists a demarcation line for the comparison of the bubble period and the reference period (the bubble period without viscous layer under the same initial bubble–wall distance), and a logarithmic relationship is observed that $\delta \propto \log_{10} \mu ^*$, where $\delta =h/R_{max}$ is the thickness of the viscous layer h normalised by the maximum bubble radius $R_{max}$, $\mu ^* = \mu /({R_{max }}\sqrt {{\rho }{{\mathop {P}\nolimits } _{{atm}}}})$ is the dynamic viscosity $\mu$ normalised by water density $ \rho $ and atmospheric pressure $P_{atm}$. The results of this paper can provide technical support for related studies of hydraulic cavitation erosion.
A dual-beam platform is developed for all-optical Thomson/Compton scattering, with versatile parameter tuning capabilities including electron energy, radiation energy, radiation polarization, etc. By integrating this platform with a 200 TW Ti:sapphire laser system, we demonstrate the generation of inverse Compton scattering X-/gamma-rays with tunable energies ranging from tens of keV to MeV. The polarization of X-/gamma-rays is manipulated by adjusting the polarization of the scattering laser. In the near future, by combining this platform with multi-PW laser facilities, our goal is to explore the transition from nonlinear Thomson scattering to nonlinear Compton scattering, ultimately verifying theories related to strong-field quantum electrodynamics effects induced by extreme scattering.
While there is evidence that childhood maltreatment (CM) is positively associated with drug use (DU), the strength and difference of the association between CM and its subtypes (hereafter CM + ST) and DU remains to be further explored. A multilevel meta-analysis was conducted on 101 independent studies reporting 333 effect sizes (N = 132,341; Mage = 24.65; 43.80%males). Results showed significantly positive correlations between CM + ST and DU (range from 0.109 to 0.185). The results of the subgroup analysis revealed notable disparities in the correlations between distinct CM subtypes and DU (F = 5.358, P<0.01). Specifically, the effect size for childhood sexual abuse (CSA) was significantly lower than childhood emotional maltreatment (CEM) and childhood physical maltreatment (CPM), while no significant difference was noted between the CEM and CPM groups. These effect sizes also varied across regions, drug types, gender, detection rate of CM, the presence or absence of alcohol in substances, publication status and measurement method. The significant yet differing correlations between different subtypes of CM and DU to some extent support the principle of equality in psychopathology. These findings help explain the relationship between CM + ST and DU laying the groundwork for further research into the intricate and complex associations between CM and DU.
Multimorbidity, especially physical–mental multimorbidity, is an emerging global health challenge. However, the characteristics and patterns of physical–mental multimorbidity based on the diagnosis of mental disorders in Chinese adults remain unclear.
Methods
A cross-sectional study was conducted from November 2004 to April 2005 among 13,358 adults (ages 18–65years) residing in Liaoning Province, China, to evaluate the occurrence of physical–mental multimorbidity. Mental disorders were assessed using the Composite International Diagnostic Interview (version 1.0) with reference to the Diagnostic and Statistical Manual of Mental Disorders (3rd Edition Revised), while physical diseases were self-reported. Physical–mental multimorbidity was assessed based on a list of 16 physical and mental morbidities with prevalence ≥1% and was defined as the presence of one mental disorder and one physical disease. The chi-square test was used to calculate differences in the prevalence and comorbidity of different diseases between the sexes. A matrix heat map was generated of the absolute number of comorbidities for each disease. To identify complex associations and potential disease clustering patterns, a network analysis was performed, constructing a network to explore the relationships within and between various mental disorders and physical diseases.
Results
Physical–mental multimorbidity was confirmed in 3.7% (498) of the participants, with a higher prevalence among women (4.2%, 282) than men (3.3%, 216). The top three diseases with the highest comorbidity rate and average number of comorbidities were dysphoric mood (86.3%; 2.86), social anxiety disorder (77.8%; 2.78) and major depressive disorder (77.1%; 2.53). A physical–mental multimorbidity network was visually divided into mental and physical domains. Additionally, four distinct multimorbidity patterns were identified: ‘Affective-addiction’, ‘Anxiety’, ‘Cardiometabolic’ and ‘Gastro-musculoskeletal-respiratory’, with the digestive-respiratory-musculoskeletal pattern being the most common among the total sample. The affective-addiction pattern was more prevalent in men and rural populations. The cardiometabolic pattern was more common in urban populations.
Conclusions
The physical–mental multimorbidity network structure and the four patterns identified in this study align with previous research, though we observed notable differences in the proportion of these patterns. These variations highlight the importance of tailored interventions that address specific multimorbidity patterns while maintaining broader applicability to diverse populations.
Objectives/Goals: Our study’s objective is to evaluate RadOnc-GPT, a GPT-4o powered LLM, in generating responses to in-basket messages related to prostate cancer treatment in the Radiation Oncology department. By integrating it with electronic health record (EHR) systems, the goal is to assess its impact on clinician workload, response quality, and efficiency in healthcare communication. Methods/Study Population: RadOnc-GPT was integrated with patient EHRs from both hospital-wide and radiation-oncology-specific databases. The study examined 158 pre-recorded in-basket message interactions from 90 non-metastatic prostate cancer patients. Quantitative natural language processing analysis and two randomized single-blinded grading studies, involving four clinicians and four nurses, were conducted to evaluate RadOnc-GPT’s response quality in completeness, correctness, clarity, empathy, and estimated editing time. Response times were measured to estimate the time saved for clinicians and nurses. The study population included patient messages across all phases of care (pre-, during, and post-treatment) for those undergoing radiotherapy. Results/Anticipated Results: In the single-blinded grader study, clinician graders evaluated 316 responses (158 from human care teams and 158 from RadOnc-GPT). Results showed RadOnc-GPT outperformed human responses in empathy and clarity, while humans excelled in completeness and correctness. Sentiment analyses using TextBlob and VADER revealed RadOnc-GPT responses had a positive mean score of 0.25, whereas human responses clustered around neutral. VADER analysis indicated a high median score for RadOnc-GPT, nearing 1.0, reflecting predominantly positive sentiment, while human responses displayed a broader sentiment range, indicating sensitivity to context. Clinicians averaged 3.60 minutes (SD 1.44) to respond, compared to 6.39 minutes (SD 4.05) for nurses, highlighting RadOnc-GPT’s efficiency in generating timely responses. Discussion/Significance of Impact: RadOnc-GPT effectively generated responses to individualized patient in-basket messages, comparable to those from radiation oncologists and nurses. While human oversight is still necessary to avoid errors, RadOnc-GPT can speed up response times and reduce pressure on care teams, shifting their role from drafting to reviewing responses.
This study explores an interesting fluid–structure interaction scenario: the flow past a flexible filament fixed at two ends. The dynamic performance of the filament under various inclination angles ($\theta$) was numerically investigated using the immersed boundary method. The motion of the filament in the $\theta$–$Lr$ space was categorised into three flapping modes and two stationary modes, where $Lr$ is the ratio of filament length to the distance between its two ends. The flow fields for each mode and their transitions were introduced. A more in-depth analysis was carried out for flapping at a large angle (FLA mode), which is widely present in the $\theta$–$Lr$ space. The maximum width $W$ of the time-averaged shape of the filament has been shown to strongly correlate with the flapping frequency. After non-dimensionalising based on $W$, the flapping frequency shows little variation across different $Lr$ and $\theta$. Moreover, two types of lift variation process were also identified. Finally, the total lift, drag and lift-to-drag ratio of the system were studied. Short filaments, such as those with $Lr\leqslant 1.5$, were shown to significantly increase lift and the lift-to-drag ratio over a wide range of $\theta$ compared with a rigid plate. Flow field analysis concluded that the increases in pressure difference on both sides of the filament, along with the upper part of the flexible filament having a normal direction closer to the $y$ direction, were the primary reasons for the increase in lift and lift-to-drag ratio. This study can provide some guidance for the potential applications of flexible structures.
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).
Depression has been linked to disruptions in resting-state networks (RSNs). However, inconsistent findings on RSN disruptions, with variations in reported connectivity within and between RSNs, complicate the understanding of the neurobiological mechanisms underlying depression.
Methods
A systematic literature search of PubMed and Web of Science identified studies that employed resting-state functional magnetic resonance imaging (fMRI) to explore RSN changes in depression. Studies using seed-based functional connectivity analysis or independent component analysis were included, and coordinate-based meta-analyses were performed to evaluate alterations in RSN connectivity both within and between networks.
Results
A total of 58 studies were included, comprising 2321 patients with depression and 2197 healthy controls. The meta-analysis revealed significant alterations in RSN connectivity, both within and between networks, in patients with depression compared with healthy controls. Specifically, within-network changes included both increased and decreased connectivity in the default mode network (DMN) and increased connectivity in the frontoparietal network (FPN). Between-network findings showed increased DMN–FPN and limbic network (LN)–DMN connectivity, decreased DMN–somatomotor network and LN–FPN connectivity, and varied ventral attention network (VAN)–dorsal attentional network (DAN) connectivity. Additionally, a positive correlation was found between illness duration and increased connectivity between the VAN and DAN.
Conclusions
These findings not only provide a comprehensive characterization of RSN disruptions in depression but also enhance our understanding of the neurobiological mechanisms underlying depression.
This study aims to assess the therapeutic effects of probiotic oral therapy in paediatric patients with anorexia nervosa (AN) and to investigate its impact on intestinal flora composition, brain–gut peptide levels and overall clinical outcomes. A retrospective study was conducted involving 100 children diagnosed with AN at Xingtang County People’s Hospital between January 2023 and June 2024. Patients were divided into two groups: a control group (n 50) receiving zinc gluconate oral solution alone and an observation group (n 50) receiving zinc gluconate plus probiotics. Outcome measures included intestinal flora analysis, brain–gut peptide levels (somatostatin (SS) and nitric oxide (NO)), clinical efficacy, serum trace element levels (Ca, Zn and Fe) and prognosis, including recurrence rates 6 months post-treatment. Baseline characteristics were similar between the two groups (P > 0·05). After treatment, the observation group showed significantly higher levels of Bifidobacterium and Lactobacillus and lower levels of Enterobacter compared with the control group (P < 0·05). Additionally, the observation group had lower levels of SS and NO (P < 0·05), indicating improved brain–gut communication. Clinical efficacy was significantly higher in the observation group (P < 0·05), with improved serum trace element levels (P < 0·05 for Ca, Zn and Fe). Furthermore, the recurrence rate 6 months post-treatment was significantly lower in the observation group compared with the control group (P < 0·05). Probiotic supplementation in children with AN effectively modulates intestinal flora, improves brain–gut peptide levels and enhances clinical outcomes.