ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective This study aimed to investigate the genetic diversity, differentiation, and population structure of Aedes albopictus across different geographical regions in Shandong Province, and to explore the relationship between genetic diversity and geographical distribution. Methods Between July and August 2024, ten Ae. albopictus populations were sampled from seven cities in Shandong Province. Genomic DNA was extracted from individual mosquitoes, and the mitochondrial cytochrome c oxidase subunit I(COⅠ)gene was amplified using PCR and sequenced. The obtained sequences were verified using BLAST and analyzed with MAFFT, MEGA 11, DnaSP v6.12, Arlequin 3.5, PopART 1.7, STRUCTURE 2.3.4 and the R packages adegenet and vegan to assess genetic diversity and population structure. Results A total of 229 COⅠ sequences(662 bp) was obtained, revealing ten variable sites with no insertions or deletions. The overall base composition showed an AT bias of 67.7%. Haplotype analysis identified 11 haplotypes, with Hap2 being the dominant and most widely distributed haplotype across all populations. Neutrality tests showed significant population expansion only in the Rizhao population. Mantel testing result revealed that geographical distance does not significantly impede gene flow. Overall, genetic differentiation among populations was low, indicating frequent gene flow. When combined with additional samples from Shanghai, Fujian, Guangdong, Yunnan, Hainan and Guangxi, STRUCTURE, UPGMA and DAPC analyses revealed two primary genetic clusters of Ae. albopictus. Conclusions Ae. albopictus populations in Shandong Province exhibit frequent gene flow, low genetic differentiation, and relatively low overall genetic diversity. However, the Rizhao population showed signs of recent expansion, highlighting the need for enhanced surveillance and targeted control measures in this area.

OBJECTIVE To provide guidance for pharmaceutical care in patients with severe Cryptococcus gattii infections.METHODS Clinical pharmacists participated in the diagnosis and treatment of a male patient with disseminated Cryptococcus gattii infection （involving the lungs and central nervous system）. Given the patient’s poor response to initial therapy， the clinical pharmacists， based on antimicrobial susceptibility test results， recommended voriconazole as an alternative azole. In response to refractory hypokalemia caused by liposomal amphotericin B， the clinical pharmacists assisted the physician in developing an intensive potassium replacement regimen. Regarding the interaction between voriconazole and nifedipine， the clinical pharmacists proactively identified the risk and intensified monitoring of the patient’s blood pressure. In response to the onset of hepatitis C during treatment， the clinical pharmacists thoroughly weighed the priority of infection treatment and recommended temporarily postponing antiviral therapy for hepatitis C. For the individualized use of voriconazole， the clinical pharmacists repeatedly performed therapeutic drug monitoring （TDM）. Regarding the patient’s poor lesion resolution， the clinical pharmacists participated in multidisciplinary team discussions to clarify the indications for surgery.RESULTS The physician adopted the clinical pharmacists’ recommendations. Following pharmacological treatment and surgical intervention， the patient’s condition stabilized， and he was discharged while still on medication.CONCLUSIONS For severe Cryptococcus gattii infections， clinical pharmacists should focus on pathogen characteristics， strengthen adverse reaction management， pay close attention to drug interactions， conduct TDM， and actively participate in multidisciplinary team collaboration to ensure the safety and efficacy of patient treatment.

Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

Objective To explore the influencing factors of immune-associated thyroid dysfunction caused by sintilimab treatment in solid tumors and construct a prediction model.Methods Medical records of patients diagnosed with solid tumors and treated with sintilimab at Peking University People's Hospital(Xizhimen Campus,Tongzhou Campus,Shijiazhuang Campus)from January 2023 to September 2024 were collected to explore the influencing factors that caused immune-related thyroid dysfunction using univariate and multifactorial binary logistic regression analyses and to establish a prediction model.The predictive effect of the model was assessed using the receiver operating characteristic(ROC)curve.Results A total of 120 patients were included,and 33 presented with immune-related thyroid dysfunction.Multifactorial logistic regression analysis revealed that thyroid-stimulating hormone(TSH)[OR=2.470,95%CI=(1.279,4.771)]and treatment cycles[OR=1.298,95%CI=(1.117,1.509)]were independent risk factors for the occurrence of immune-associated thyroid dysfunction,and the difference was statistically significant(P＜0.05).The area under the ROC curve was(0.897±0.043)[95%CI=(0.813,0.981)],the Yoden index was 0.703,and the model prediction accuracy was 86.5%.Conclusion The risk of immune-related thyroid dysfunction caused by sintilimab is high,and TSH and treatment cycle are the influencing factors,and the constructed model has certain predictive value and is of reference significance.

OBJECTIVE To investigate the neuroprotective effects of Ditan Decoction(DTD)on ischemic stroke.METHODS A mouse middle cerebral artery occlusion(MCAO)model was used to induce cerebral ischemia and assess the role of DTD in post-stroke NVU injury.DTD was gavaged once a day for 3 days after MCAO.Transwell neutrophil chemotaxis assay was used to explore the role of DTD in the neutrophil chemotaxis.RESULTS In the MCAO model,DTD treatment significantly reduced infarct volume(P<0.01)and attenuated blood-brain barrier disruption,as evidenced by decreased IgG leakage and preserved laminin expression(P<0.05).Furthermore,DTD suppressed neutrophil infiltration into ischemic brain tissue,as demonstrated by reduced neutrophil elastase(P<0.01)and myeloperoxidase(P<0.05)levels.Mechanistically,DTD inhibited neutrophil chemotaxis in a dose-dependent manner and downregulated phosphodiesterase 4B(PDE4B),a key regulator of neutrophil migration(P<0.05).Molecular docking analysis i-dentified four active DTD components-apigenin,vitexin,chlorogenic acid,and orientin-with strong binding affinities to PDE4B(bind-ing energies<-5 kcal·mol-1),suggesting their potential role in mediating DTD's therapeutic effects.CONCLUSION These find-ings highlight DTD as a promising intervention for ischemic stroke,targeting NVU preservation and PDE4B-dependent neutrophil mod-ulation.

The deep integration of party building and business operations is a crucial pathway to strengthen party building in public hospitals and promote high-quality hospital development under the new situation.This article takes the"Hongyan Van-guard Inter-hospital Transfer Service Task Force for Critically Ill Patients"of The Second Hospital of Chongqing Medical Universi-ty as the research object.Based on cross-branch collaboration practices,it systematically constructs a three-dimensional integra-tion model of"goal synergy-organizational reconstruction-capability closed-loop"and deeply analyzes the internal logic of party building leading business challenges.The research uses party building as the ideological guide and organizational reconstruction as an important measure to establish a standardized transfer process and a digital quality control system.Data shows that more than 150 cases of inter-hospital transfers of critically ill patients have been completed within a year,with a growth rate exceeding 40％.Patient satisfaction reached 98.7％,and the CMI value improved significantly.This provides an empirical model for public hospitals to solve the collaboration problems between cross-functional departments and clinical frontline departments,and achieve the"double helix"development of party building and business operations.

OBJECTIVE To investigate the neuroprotective effects of Ditan Decoction(DTD)on ischemic stroke.METHODS A mouse middle cerebral artery occlusion(MCAO)model was used to induce cerebral ischemia and assess the role of DTD in post-stroke NVU injury.DTD was gavaged once a day for 3 days after MCAO.Transwell neutrophil chemotaxis assay was used to explore the role of DTD in the neutrophil chemotaxis.RESULTS In the MCAO model,DTD treatment significantly reduced infarct volume(P<0.01)and attenuated blood-brain barrier disruption,as evidenced by decreased IgG leakage and preserved laminin expression(P<0.05).Furthermore,DTD suppressed neutrophil infiltration into ischemic brain tissue,as demonstrated by reduced neutrophil elastase(P<0.01)and myeloperoxidase(P<0.05)levels.Mechanistically,DTD inhibited neutrophil chemotaxis in a dose-dependent manner and downregulated phosphodiesterase 4B(PDE4B),a key regulator of neutrophil migration(P<0.05).Molecular docking analysis i-dentified four active DTD components-apigenin,vitexin,chlorogenic acid,and orientin-with strong binding affinities to PDE4B(bind-ing energies<-5 kcal·mol-1),suggesting their potential role in mediating DTD's therapeutic effects.CONCLUSION These find-ings highlight DTD as a promising intervention for ischemic stroke,targeting NVU preservation and PDE4B-dependent neutrophil mod-ulation.

Pregnancy with chronic kidney disease (CKD), particularly in stages 4-5, carries high risks of adverse outcomes including maternal renal failure, preeclampsia/eclampsia, fetal growth restriction, and preterm birth. This report described a 26-year-old woman with congenital solitary kidney, polycystic ovaries, and uterine septum due to PAX2 gene variant, complicated by CKD stage 4. Through multidisciplinary team precision management and individualized treatment strategies, including timely initiation of dialysis, the patient successfully maintained pregnancy until 34 +1 weeks and delivered a female infant via cesarean section. This case summarizes key management experiences for end-stage renal disease in pregnancy, highlighting early risk assessment, precise nutritional management, hemodialysis protocol optimization, and the crucial role of multidisciplinary collaboration, providing valuable references for managing CKD-complicated pregnancies.