Soy is a vital source of plant carbohydrates.However,it poses significant allergenic risks,particularly to young children and animals.Among the various proteins in soy,β-conglycinin,which con-stitutes approximately 30％of total soy carbohydrates,is a primary allergen.Undigested β-conglycinin can lead to intestinal damage by inhibiting cell growth,disrupting the cytoskeleton,and inducing apopto-sis.It can also enter the lymphatic and circulatory systems,triggering allergic reactions.Conventional ELISA methods for detecting β-conglycinin rely on polyclonal or monoclonal antibodies,which are limited by their large molecular weight,difficulty in accessing the protein core,and sensitivity to acidic and bas-ic conditions.To address these limitations,this study aimed to develop nanobodies(Nbs)against β-con-glycinin.Nbs,derived from the variable regions of heavy-chain antibodies found in camelids,have a mo-lecular weight approximately one-tenth that of conventional antibodies.They offer advantages such as small size,stable structure,high specificity,and strong affinity.A female alpacas was immunized five times using β-conglycinin,which showed a heavy chain antibody potency of 1∶16 000 by ELISA.Pe-ripheral blood lymphocytes were subsequently isolated and total RNA was extracted.The variable region of the heavy-chain antibody was amplified via PCR,and recombinant plasmids were constructed and transformed into the E.coli competency strain ER2738.The resulting library contained about 3.5×108 CFU/mL,which increased to 1.15×1012 PFU/mL after phage rescue,with a 100％Nbs gene insertion rate,indicating high diversity.Its Nbs phage output was significantly enriched by four rounds of solid-phase elution with an enrichment rate of 155.9.Four rounds of solid-phase panning yielded 35 positive clones,all of which shared the same amino acid sequence upon sequencing.The selected Nb was ex-pressed in a prokaryotic system,and its binding ability to β-conglycinin was confirmed using Western blotting and ELISA.The results demonstrated excellent specificity and affinity.This research lays the groundwork for developing a rapid and efficient detection method for β-conglycinin using Nbs,potentially enhancing food safety and allergen management.

Objective:To evaluate the effectiveness of a workshop-driven interactive teaching model in clinical alarm training for undergraduate nursing interns in the intensive care unit (ICU).Methods:A total of 120 undergraduate nursing students who interned in the ICU from November 2023 to April 2024 were enrolled and randomly assigned using a random number table into a control group ( n=60, traditional teaching) and an intervention group ( n=60, workshop-driven interactive teaching). Clinical alarm knowledge, attitudes, and practices (KAP); perception of patient safety culture; and training satisfaction were assessed before and after the training using validated questionnaires. Differences between groups were analyzed using independent sample t-test, paired sample t-test, chi-square test, and the Mann-Whitney U test with SPSS 22.0. Results:There were no significant differences between the two groups in clinical alarm KAP scores or patient safety culture perception scores before the training ( P>0.05). After the training, the intervention group showed significantly higher scores in clinical alarm KAP [(127.58±6.45) vs. (123.48±7.61), t=3.17, P=0.002] and patient safety culture perception [(99.44±9.17) vs. (95.45±12.03), t=-2.04, P=0.044] compared with the control group. Satisfaction with training content, teaching quality, and overall instructional design was significantly higher in the intervention group than in the control group ( P<0.05). Within-group comparisons showed that the intervention group had significant improvements in clinical alarm KAP [(127.58±6.45) vs. (120.10±10.25), t=-5.10, P<0.001] and patient safety culture perception [(99.44±9.17) vs. (94.46±12.12), t=-2.65, P=0.010] after training. No significant changes were observed in the control group after training ( P>0.05). Conclusions:The workshop-driven interactive teaching model can effectively enhance the clinical alarm KAP levels and patient safety culture perception among undergraduate nursing interns in the ICU. This teaching approach provides a scientific basis for optimizing clinical alarm education and cultivating high-quality nursing professionals.

Hypochlorous acid/hypochlorite(HClO/ClO-)plays a key role in biological processes and is commonly used as a disinfectant in drinking water.However,excessive intake of HClO/ClO-can oxidize biomolecules like DNA,RNA,and proteins,causing organ damage.Diseases such as rheumatoid arthritis and Alzheimer's disease can also lead to overproduction of HClO/ClO-.Therefore,accurately detecting HClO/ClO-levels is crucial.In this study,an HClO/ClO-fluorescent probe,NC-TPA-PPh3,was designed and synthesized,with a triphenylamine core as the fluorescent unit,carbon-carbon double bonds as recognition sites,and a quaternary ammonium salt for mitochondria targeting,forming a D-π-A structure.This probe had a fluorescence lifetime of 3.71 ns and a fluorescence quantum yield of 0.51.Upon exposure to HClO/ClO-,the maximum fluorescence emission wavelength of the probe in DMSO/H2O(9∶1,V/V,pH=7.4)solution(20 μmol/L)shifted from 550 nm to 430 nm,with a fluorescence intensity increase of 35.7 times compared to blank probe solution,allowing for selective recognition of HClO/ClO-.The probe also exhibited a large Stokes shift(130 nm)and a low limit of detection(LOD)of 9.16×10-8 mol/L.Based on characterization by proton nuclear magnetic resonance(1H NMR),electrospray ionization-mass spectrometry(ESI-MS),scanning electron microscopy(SEM)and theoretical calculations,it was speculated that NC-TPA-PPh3 recognized HClO/ClO-through oxidative cleavage of the C=C bond in the probe,generating TPA-CHO with lower water solubility and a smaller conjugated structure.This disrupted the D-π-A structure,blocking intramolecular charge transfer(ICT),causing the fluorescence emission peak to blue-shift from 550 nm to 430 nm.Additionally,this process induced an aggregation-induced fluorescence effect,significantly enhancing the fluorescence intensity at 430 nm.

Objective To analyze the characteristics of TCM symptoms of aging in female insomnia patients;To provide syndrome differentiation evidence for clinical prevention and treatment of female aging.Methods A cross-sectional study method was used to include female insomnia patients who attended outpatient clinics at Dongzhimen Hospital of Beijing University of Chinese Medicine,Beijing Changping District Hospital of Traditional Chinese Medicine,and the Third Affiliated Hospital of Beijing University of Chinese Medicine from August 2021 to July 2024.The patients'clinical information was collected,and frequency analysis,factor analysis,and clustering analysis of the relevant clinical information of the 107 female insomnia patients were conducted,which,together with the experts'opinions,resulted in characteristics of TCM syndrome elements and syndrome distribution of aging in female insomnia patients.Results Totally 20 core items were screened and 7 common factors were obtained from the factor analysis.There were 5 types of syndrome elements of disease location associated with aging symptoms in female patients with insomnia,including heart,liver,spleen,kidney and lung;and there were 7 types of syndrome elements of disease property,including qi deficiency,yin deficiency,qi stagnation,blood deficiency,heat,phlegm,and dampness.There were 4 types of syndromes were obtained from the systematic clustering,including heart-kidney disharmony syndrome,heart-liver stagnation syndrome,spleen deficiency and qi stagnation syndrome,lung-spleen qi deficiency syndrome.Conclusion By analyzing the TCM syndrome characteristics of aging symptoms in female patients with insomnia,four types of syndromes are obtained.The heart-kidney disharmony syndrome is the common syndrome.The internal relationship between insomnia and aging process in female patients with insomnia is revealed from the perspective of pathogenesis,which can provide a research basis for the clinical practice of TCM anti-aging guided by syndrome differentiation and treatment in the future.

The Occupational Classification Dictionary of the People's Republic of China (2015 Edition) has added a new occupation type, Medical Nursing Assistants, aiming to meet the strong demand for medical care in the context of the aging population in China.In order to standardize the services of medical nursing assistants for the elderly in home and community settings and contribute to healthy aging, the National Health Commission issued the " Service Standards for Medical Nursing Assistants of Older Adults in Home and Community" ( WS/ T 803—2022) on September 28, 2022.The standards regulate the service processes, service items and requirements, as well as service evaluation and improvement for elderly medical nursing assistants.The interpretation of the standard's formulation background, the compilation process, and the standard's content are as follows.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

Mild cognitive impairment due to Alzheimer′s disease is an inevitable pathological stage in the early development of Alzheimer′s disease, which can be classified as "microlumps in the brain collaterals" in traditional Chinese medicine. Based on the theory of latent toxin blocking collaterals, this article discusses the etiology and pathogenesis, clinical sequelae, and traditional Chinese medicine intervention strategies for mild cognitive impairment due to Alzheimer′s disease. The onset of mild cognitive impairment due to Alzheimer′s disease is very similar to the latent pathogen theory, which states that "the latent pathogen is latent and then develops, the poison is deep and difficult to cure, and the development can be recognized but the latent pathogen cannot be detected." Combining clinical experience, our team believes that the basic nature of the disease is a slight deficiency and a slight excess of symptoms. A slight deficiency of the five zang viscera and six fu viscera as root and a latent toxin colling collaterals of qi, fire, phlegm, and blood stasis as manifestaion. These usually start from the qi depression and develop into phlegm coagulation and blood stasis, then end up in latent toxin and gradually become the healthy qi deficiency. Therefore, the deficiency of vital qi and incubation of evil, latent toxin blocking collaterals the pathogenesis of early intervention of this disease should be carried out, upholding the idea that "the upper workman treats the disease before it is diagnosed." The principle of strengthening vital qi to eliminate pathogenic factors, slowing down and promoting pathogenic factors elimination, establishing the method of supporting correctness and wisdom, simultaneously detoxifying and clearing the blood stasis, pattern differentiation as the main and the disease differentiation as the first, combining the disease and pattern, and adjusting the macroscopic and microscopic, focusing simultaneously on eliminating and replenishing, dispel phlegm and remove blood stasis, achieve a strong vital qi and the elimination of evil, and enhance intelligence, delay or even block the progression of mild cognitive impairment due to Alzheimer′s disease, improve patients′ quality of life, and provide a theoretical basis for the early clinical prevention and treatment of Alzheimer′s disease.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.