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Polyethyleneimine-functionalized cellulose beads (PCB-PEI) with hierarchical multi-porous structures were fabricated via a novel strategy combining intermolecular pre-crosslinking with glutaraldehyde chemical crosslinking to improve the specific surface area and mechanical performances of PCB-PEI. The resultant PCB-PEI possessed unique hierarchical architecture consisting of surface interpenetrating porous networks, resulting in large specific surface area of 100.61 m2/g and high porosity of 94.27%. In particular, the robust double cross-linking networks endowed PCB-PEI with outstanding stiffness, toughness, and elasticity. The compressive strength was up to 202 kPa, and retained at 94.5 kPa with 84.1% of shape recovery after 10 loading–unloading cycles at 50% compressive strain. Benefiting from its hierarchical multi-porous structure, abundant functional sites, and excellent mechanical properties, PCB-PEI displayed excellent dye adsorption and reusability. The maximum adsorption capacities for methyl blue (MB) and rose bengal (RB) reached 1550.55 and 467.95 mg/g. After 8 cycles, the adsorption capacities of PCB-PEI for MB and RB still maintained more than 97% and 86%, respectively. Predominant electrostatic attraction and hydrogen bond interactions during adsorption process were proposed to improve the adsorption of dyes. Thus, PCB-PEI is a potential, sustainable adsorbent for highly efficient removal of dyes from wastewater.Graphic abstract

Background The heterogeneity of cognitive impairments in schizophrenia has been widely observed. However, reliable cognitive boundaries to differentiate the subgroups remain elusive. The key challenge for cognitive subtyping is applying an integrated and standardized cognitive assessment and understanding the subgroup-specific neurobiological mechanisms. The present study endeavors to explore cognitive subgroups and identify their morphological features. Methods A total of 920 schizophrenia patients and 169 healthy controls were recruited. MATRICS Consensus Cognitive Battery was applied to assess cognitive performance and recognize cognitive subgroups through latent profile and latent transition analysis. Cortical thickness and gray matter volume were employed for the morphological features across subgroups. Results Four reproducible cognitive subgroups were identified, including multidomain-intact, executive-preserved, executive-deteriorated, and multidomain-deteriorated subgroup. After 12 weeks of follow-up, the cognitive characteristics of three out of the four subgroups kept stability, except for multidomain-deteriorated subgroup in which 48.8% of patients with improved cognition transited into the executive-deteriorated subgroup. Across subgroups, significant gradient features of brain structure were exhibited in fronto-temporal regions, hippocampus, and insula. Compared to healthy controls, multidomain-intact subgroup showed the most intact cognition and morphology, and multidomain-deteriorated subgroup with youngest age showed morphological decline in extensive regions. The remaining two subgroups showed intermediate cognitive performance, but could be distinguished by executive function and morphological differences in posterior cingulate cortex. Conclusions Our study provides novel insights into the heterogeneity of cognitive impairments in schizophrenia and the morphological features from cross-sectional and longitudinal levels, which could advance our understanding of complex cognition-morphology relationships and guide personalized interventions.

Antipsychotic intake may induce weight gain in drug-naive individuals with schizophrenia, leading to poor compliance in clinical management. However, there is still a lack of effective approaches to treat or prevent this side-effect. Therefore, we conducted this pilot study to investigate the effect of continuous theta burst stimulation (cTBS), a non-invasive magnetic stimulation technique, on preventing olanzapine-induced weight gain. Thirty-nine first-episode drug-naive individuals with schizophrenia were randomly assigned to receive either the active or sham cTBS intervention for 25 sessions (5 times per day for 5 consecutive days). The primary outcomes were changes in body weight and body mass index (BMI). Secondary outcomes included psychiatric symptoms, eating behavior scales, behavior tasks, and metabolic measures. For the result, the body weight and BMI increased significantly in the sham group but not in the active group, with a significant group effect. The active group exhibited a selective increase in the cognitive restraint domain in the Three-Factor Eating Questionnaire (TFEQ-CR) and a decrease in stop-signal reaction time compared to the sham group. The effect of cTBS on body weight was mediated by TFEQ-CR. Our findings demonstrated the feasibility that cTBS intervention could be a potential method for preventing olanzapine-induced weight gain in drug-naive first-episode schizophrenia patients through enhancing cognitive restraint to food. Trial registration: clinical trial registered with clinicaltrials.gov (NCT05086133).

Abstract Background and Hypothesis Obesity is a common comorbidity in individuals with schizophrenia and is associated with poor clinical outcomes. At present, there are limited effective approaches for addressing this issue. We conducted a double-blind, randomized, sham-controlled clinical trial to investigate the efficacy of noninvasive magnetic stimulation techniques in reducing obesity in individuals with schizophrenia. Study Design Forty overweight individuals with schizophrenia were recruited and randomly assigned to receive either the active or sham intervention. The active group received 50 accelerated continuous theta burst stimulation (cTBS) sessions over the left primary motor area (M1), while the sham group received sham stimulation. The primary outcomes were the change in body weight and body mass index (BMI), and the secondary outcomes were the psychiatric symptoms, eating behavior scales, metabolic measures, and electrophysiological to food picture stimuli. Study Results The study demonstrated a significant decrease in body weight and BMI after the intervention selectively in the active group (mean = −1.33 kg, P = .002), and this improvement remained at the 1-month follow-up (mean = −2.02 kg, P = .008). The score on the Barratt Impulsivity Scale (mean = −1.78, P = 0.036) decreased in the active group and mediated the effect of accelerated cTBS on body weight. In the food picture cue electroencephalograph task, the late positive potential component, which is related to motivated attention and emotional processing, decreased in frontal brain regions and increased in posterior regions after the active intervention. Conclusions The accelerated cTBS may offer a promising approach for treating obesity in individuals with schizophrenia. Further research with a larger sample size or individualized stimulation protocol should be promising. Trial Registration Clinical trial registered with clinicaltrials.gov (NCT05086133).

The brain neurotramsmitter dopamine may play an important role in modulating systemic glucose homeostasis. In seven hundred and four drug- naïve patients with first-episode schizophrenia, we provide robust evidence of positive associations between negative symptoms of schizophrenia and high fasting blood glucose. We then show that glucose metabolism and negative symptoms are improved when intermittent theta burst stimulation (iTBS) on prefrontal cortex (PFC) is performed in patients with predominantly negative symptoms of schizophrenia. These findings led us to hypothesize that the prefrontal cortical dopamine deficit, which is known to be associated with negative symptoms, may be responsible for abnormal glucose metabolism in schizophrenia. To explore this, we optogenetically and chemogenetically inhibited the ventral tegmental area (VTA)-medial prefrontal cortex (mPFC) dopamine projection in mice and found both procedures caused glucose intolerance. Moreover, microinjection of dopamine two receptor (D2R) neuron antagonists into mPFC in mice significantly impaired glucose tolerance. Finally, a transgenic mouse model of psychosis named Disc1 tr exhibited depressive-like symptoms, impaired glucose homeostasis, and compared to wild type littermates reduced D2R expression in prefrontal cortex.

Multimodal large language models (MLLMs) have shown strong potential for medical image reasoning, yet fairness across demographic groups remains a major concern. Existing debiasing methods often rely on large labeled datasets or fine-tuning, which are impractical for foundation-scale models. We explore In-Context Learning (ICL) as a lightweight, tuning-free alternative for improving fairness. Through systematic analysis, we find that conventional demonstration selection (DS) strategies fail to ensure fairness due to demographic imbalance in selected exemplars. To address this, we propose Fairness-Aware Demonstration Selection (FADS), which builds demographically balanced and semantically relevant demonstrations via clustering-based sampling. Experiments on multiple medical imaging benchmarks show that FADS consistently reduces gender-, race-, and ethnicity-related disparities while maintaining strong accuracy, offering an efficient and scalable path toward fair medical image reasoning. These results highlight the potential of fairness-aware in-context learning as a scalable and data-efficient solution for equitable medical image reasoning.

Promptable segmentation foundation models such as SAM3 have demonstrated strong generalization capabilities through interactive and concept-based prompting. However, their direct applicability to medical image segmentation remains limited by severe domain shifts, the absence of privileged spatial prompts, and the need to reason over complex anatomical and volumetric structures. Here we present Medical SAM3, a foundation model for universal prompt-driven medical image segmentation, obtained by fully fine-tuning SAM3 on large-scale, heterogeneous 2D and 3D medical imaging datasets with paired segmentation masks and text prompts. Through a systematic analysis of vanilla SAM3, we observe that its performance degrades substantially on medical data, with its apparent competitiveness largely relying on strong geometric priors such as ground-truth-derived bounding boxes. These findings motivate full model adaptation beyond prompt engineering alone. By fine-tuning SAM3's model parameters on 33 datasets spanning 10 medical imaging modalities, Medical SAM3 acquires robust domain-specific representations while preserving prompt-driven flexibility. Extensive experiments across organs, imaging modalities, and dimensionalities demonstrate consistent and significant performance gains, particularly in challenging scenarios characterized by semantic ambiguity, complex morphology, and long-range 3D context. Our results establish Medical SAM3 as a universal, text-guided segmentation foundation model for medical imaging and highlight the importance of holistic model adaptation for achieving robust prompt-driven segmentation under severe domain shift. Code and model will be made available at https://github.com/AIM-Research-Lab/Medical-SAM3.

Homogeneous earth-abundant metal catalysis based on well-defined molecular complexes has achieved great advance in synthetic methodologies. However, sophisticated ligand, hazardous activator and multistep synthesis starting from base metal salts are generally required for the generation of active molecular catalysts, which may hinder their broad application in large scale organic synthesis. Therefore, the development of metal cluster catalysts formed in situ from simple earth-abundant metal salts is of importance for the practical utilization of base metal resource, yet it is still in its infancy. Herein, a mixture of catalytic amounts of cobalt (II) iodide and potassium tert-butoxide is discovered to be highly active for selective hydroboration of vinylarenes and dihydroboration of nitriles, affording a good yield of diversified hydroboration products that without isolation can readily undergo further one pot transformations. It should be highlighted that the alkoxide-pinacolborane combination acts as an efficient activation strategy to activate cobalt (II) iodide for the generation of metastable heterotopic cobalt catalysts in situ, which is proposed to be catalytically active species. Homogeneous earth-abundant metal catalysis based on well-defined metal complexes is of interest for organic synthesis, but typically employs expensive catalysts, air sensitive or synthetically challenging chemicals. Here, the authors report an efficient and regio-selective catalytic system for hydroboration of vinylarenes and organic nitriles with HBPin, using commercially available CoI 2 and KO t Bu under ligand-free conditions.

Immune cell metabolism plays a pivotal role in regulating cellular proliferation, differentiation, and functional responses, collectively shaping immune responses within the tumor microenvironment (TME). Recent advancements increasingly highlight diverse metabolic phenotypes of immune cells and their complex interplay with tumor dynamics. Immune cell metabolism exhibits remarkable plasticity, enabling metabolic networks to finely tune immune cell behaviors in response to external stimuli. Furthermore, a strong correlation between metabolic profiles and immune cell fate, activation, and function has been repeatedly delineated in immunometabolism. Consequently, targeting the metabolic networks, referred to as metabolic checkpoints, to reprogram immune cell phenotypes and bolster antitumor immunity holds significant promise for clinical translation. This review summarizes the latest developments in multifaceted metabolic checkpoints, with a focus on how metabolic checkpoints modulate immunological consequences and cancer progression. Lastly, potential strategies for targeting metabolic checkpoints are explored to inspire innovative approaches in immunotherapy.

Drought stress severely impacts plant productivity, particularly in non-cultivated species such as .L. However, the role of rhizosphere and endophytic bacterial communities in enhancing drought tolerance remains underexplored. We used 16S rRNA amplicon sequencing to investigate microbial communities in the rhizosphere, roots, bulbs, and leaves of under simulated drought conditions using PEG-6000 (CK, 5%, 15%, 25%) and post-rehydration recovery. Alpha and beta diversity, phylogenetic relationships, and functional predictions were analyzed. Drought stress reduced rhizosphere bacterial diversity by 42% but increased leaf diversity by 52%. The 15% PEG treatment marked a key threshold for community shifts. and were significantly enriched under drought, and functional predictions indicated their involvement in osmotic regulation and phytohormone synthesis. Post-rehydration partially restored microbial composition in aerial tissues but not in the rhizosphere. These findings suggest that drought induces niche-specific microbial adaptations and that bacterial community structure plays a critical role in drought resilience. This study provides insights into plant-microbe interactions and offers a basis for developing microbial strategies to improve drought tolerance in species.