OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

BackgroundEmotional disorders in adolescents have emerged as a prominent issue in recent years. Current mainstream clinical assessment approaches for such conditions predominantly rely on interviews and rating scales， which are limited by inherent drawbacks such as high subjectivity and recall bias. Accordingly， there exists an urgent clinical need for the development of objective， quantifiable auxiliary diagnostic tools.In previous studies， frontal electroencephalography （EEG） has demonstrated significant value in assessing depressive and anxiety. However， the lack of standardized quantitative metrics and intuitive visual analytical approaches has severely restricted clinical interpretability of EEG data and diminished patient engagement. To address these key limitations， the present study proposes an innovative analytical framework that converts frontal EEG signals into quantifiable visual metrics to enhance clinical comprehension and acceptance. ObjectiveTo explore the value of frontal EEG in assessing anxiety， depression， and sleep quality in adolescents with emotional disorders， with the aim of providing objective auxiliary tools for clinical diagnosis and assessment of adolescents with emotional disorders. MethodsThis cross-sectional study recruited 105 adolescents aged 12-18 years who visited the outpatient department of a specialized mental hospital in Beijing from April 2023 to April 2024. All participants met the diagnostic criteria for mood （affective） disorders or anxiety disorders in the International Classification of Diseases， tenth edition （ICD-10）. Frontal EEG signals were collected within a big data analytics-driven framework and further processed by EEG system to generate six quantitative cerebral function indices， namely brain load， tension and excitement， emotional stress， sleepiness index， cerebral vitality， and cerebral fatigue. In addition， validated standardized scales， including the Self-rating Anxiety Scale （SAS）， the Self-rating Depression Scale （SDS）， and the Pittsburgh Sleep Quality Index （PSQI）， were administered for anxiety， depressive symptoms， and sleep quality， respectively. ResultsIn adolescent patients with emotional disorders， the SAS score exhibited significant positive correlations with brain load （r_s=0.328， P<0.01）， emotional stress （r_s=0.341， P<0.01）， and cerebral fatigue （r_s=0.286， P<0.01）. The SDS score was positively correlated with brain load （r_s=0.275， P<0.01）， emotional stress （r_s=0.241， P<0.05）， and cerebral fatigue （r_s=0.311， P<0.01）， while showing a significant negative correlation with cerebral vitality （r_s=-0.212， P<0.05）. Additionally， the PSQI total score demonstrated positive correlations with brain load （r_s=0.340， P<0.01）， emotional stress （r_s=0.322， P<0.01）， and cerebral fatigue （r_s=0.229， P<0.05）. ConclusionFrontal EEG-derived indices， including brain load， emotional stress， cerebral fatigue and cerebral vitality， may serve as objective markers for reflecting anxiety， depression， and sleep quality in adolescents with emotional disorders. ［Funded by Beijing High level Innovation and Entrepreneurship Talent Support Program （number， 202504841041）； Horizontal Joint Project］

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

OBJECTIVE To provide references for ensuring the safety of prescription preparation， dispensing， and use of parenteral nutrition solution， as well as for expanding the scope of pharmaceutical services provided by pharmacists in the Pharmacy Intravenous Admixture Services （PIVAS）. METHODS Under the guidance of PIVAS pharmacists， the rules for reviewing medical orders of parenteral nutrition in the PIVAS system and the information displayed on the infusion labels of finished parenteral nutrition solutions were refined. The process management of dispensing parenteral nutrition solution was strengthened， and detailed quality control and inspection rules were formulated. Additionally， Clinical Safety Monitoring Form for Finished Parenteral Nutrition Infusions was designed to conduct clinical monitoring and inspections for abnormalities in the finished infusions， infusion operations， and complications that may arise during the use of finished parenteral nutrition infusions. The implementation effects of the aforementioned optimization/inspection measures were evaluated by comparing data on the efficiency of medical order review for parenteral nutrition， the rate of irrational medical orders， the compliance rate of vascular access selection and infusion rate standardization， the rate of dispensing error， as well as the abnormalities occurring during clinical use， before and after the optimization/inspection initiatives were put into place. RESULTS The optimized prescription review system achieved automatic review of medical orders for parenteral nutrition， enhancing the efficiency of order review. The average time taken to review one parenteral nutrition medical order was reduced from approximately 1 minute to 10 seconds. The irrational rate of parenteral nutrition orders decreased by 31.87%. The dispensing error rate of parenteral nutrition decreased by 56.55%. The standard rate of vascular access selection and standard rate of infusion speed were increased by 13.29% and 3.54%， respectively. The PIVAS pharmacists identified and intervened in 5 abnormal cases out of 298 cases examined for use of parenteral nutrition solutions. CONCLUSIONS By optimizing the prescription review system， improving labeling information， and strengthening quality control inspections during both preparation and administration processes， PIVAS pharmacists have enhanced the safety of compounded parenteral nutrition solutions. This initiative has expanded the scope and depth of pharmaceutical care provided by dispensing pharmacists.

Objective To explore the changes in neural activity in patients with type 2 diabetes mellitus(T2DM)and their corre-lation with executive function,and to analyze the neural mechanisms underlying the decline in executive function in T2DM patients.Methods Thirty-one T2DM patients(T2DM group)and thirty-two healthy controls(HC)(HC group)matched for body mass index(BMI)underwent resting-state functional magnetic resonance imaging(rs-fMRI)scans and N-back task tests were included.Differ-ences in the amplitude of low-frequency fluctuation(ALFF),regional homogeneity(ReHo),and seed-based functional connectivity(FC)between the two groups were compared,and partial correlation analyses were performed between the difference results and N-back task performance.Results The T2DM group showed prolonged reaction time(RT)in the 1-back and 2-back tasks.T2DM patients exhibited increased ALFF in the bilateral caudate nucleus,left medial superior frontal gyrus,and right postcentral gyrus,as well as elevated ReHo in the right putamen.FC analysis revealed significant alterations in FC between the caudate nucleus,putamen,and multiple brain regions in T2DM patients,with some of these FC changes significantly correlated with RT and accuracy(ACC)in the N-back task.Conclusion The decline in executive function in T2DM patients may be associated with abnormal neural activity in brain regions such as the striatum,salience network,and frontoparietal control network.FC further decreases under increased cognitive load.These findings provide evidence for the study of the neural mechanisms of executive function impairment in T2DM patients.

Objective To establish a stable liquid chromatography-tandem mass spectrometry(LC-MS/MS)method for detecting gamma-aminobutyric acid(GABA)in plasma,and to evaluate the value of GABA detection in the diagnosis of sleep disorders.Methods GABA was detected using a UPLC Xevo TQs system.The method was pre-validated and its performance was verified to establish a reference range for healthy individuals.The difference in plasma GABA levels between apparently healthy individuals and patients with sleep disorders was compared.Results We employed deuterated compounds as isotopic internal standards and utilized an Amide chromatographic column for separation.The mobile phase was 0.050%formic acid in water and 90%acetonitrile in water containing 0.175%formic acid and 5 mmol/L ammonium acetate with gradient elution in the column temperature of 35℃.The linear range for the detection of GABA by LC-MS/MS was 0.05-10.00 μmol/L,with a lower limit of quantification of 0.02 μmol/L,the inter-day CV<3.00%and intra assay CV<4.00%,respectively,and the recovery rate was 101.06%-109.02%.The reference ranges for plasma GABA were established by analyzing 300 healthy controls stratified by age:18-34 years(0.08-0.15 μmol/L),35-49 years(0.10-0.20 μmol/L),and≥50 years(0.12-0.23 μmol/L).Then plasma GABA was used as a biomarker for auxiliary diagnosis of sleep disorders in analyzing 221 patients and 300 healthy controls,which revealed that AUC values were 0.510(P=0.850),0.686(P=0.002),and 0.890(P<0.001)in the groups of 18-34 years,35-49 years,and≥50 years,respectively,with optimal cut-off values of 0.09,0.10 and 0.11 μmol/L.Conclusion A reliable LC-MS/MS method for detecting GABA has been established,which can detect plasma GABA levels sensitively and accurately and can be used in assisting the clinical diagnosis of sleep disorders.