Objective:Middle ear cholesteatoma is a common otolaryngological disease, and traditional diagnostic methods have certain limitations. This study aims to construct a computer-aided diagnosis model for middle ear cholesteatoma based on integrated convolutional neural networks (CNNs) to improve diagnostic accuracy and efficiency.Methods:Firstly, Data were collected from patients who visited the Department of Otorhinolaryngology Head and Neck Surgery at the First People′s Hospital of Yinchuan between January 2020 and December 2021. 8 000 temporal bone CT images were collected, including 5 000 images diagnosed pathologically as middle ear cholesteatoma and 3 000 normal images. A five-fold cross-validation method was used to divide the dataset into training and testing sets. Next, a transfer learning approach was used to initialize model parameters, and the AlexNet, GoogleNet, and ResNet networks were pre-trained to extract deep features from the images. Then, the Softmax classification algorithm was applied to classify the features, resulting in three independent classifiers. These classifiers were combined using an ensemble learning method with a weighted voting approach to obtain the final diagnostic results. Finally, the model was evaluated by comparing the ensemble classifier with individual classifiers to assess its accuracy, precision, sensitivity, specificity, and diagnostic time, and a comparison with low-mid-and high-experience physician groups was conducted to comprehensively evaluate the model′s diagnostic performance.Results:The experimental results showed that the model achieved an accuracy of 88.8%(178/200), precision of 92.9%,(112/120) sensitivity of 89.8%(108/120), and specificity of 88.1%(70/80). The average diagnostic time for individual patient temporal bone CT images was reduced to 2-3 seconds. Compared to the diagnostic results from low-mid-and high-experience physician groups, the model demonstrated significant advantages and effectively assisted clinicians in making rapid and accurate middle ear cholesteatoma diagnoses.Conclusion:The proposed middle ear cholesteatoma diagnostic model based on integrated convolutional neural networks exhibits high recognition accuracy and rapid diagnostic speed, significantly improving clinical diagnostic efficiency, especially in early screening and auxiliary diagnosis, making it of considerable value in clinical practice.

Objective To investigate the effect of resveratrol on the tumor microenvironment in osteosarcoma. Methods A C57BL/6 xenograft mouse model was established and treated with resveratrol. Single-cell sequencing was performed to analyze changes in the tumor microenvironment. Immunohistochemistry was used to assess immune cell infiltration, while Western blotting was conducted to examine alterations in cellular signaling pathways. Results Resveratrol significantly inhibited the proliferation of LM8 osteosarcoma cells in C57BL/6 mice compared to the control group. Additionally, CD8⁺ T cell recruitment was enhanced. The Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) signaling pathway was notably downregulated in LM8 osteosarcoma cells following resveratrol treatment. Conclusion Resveratrol promotes CD8⁺ T cell infiltration by inhibiting the JAK2/STAT3 signaling pathway, suggesting its potential as a therapeutic agent in osteosarcoma treatment.
Osteosarcoma/genetics* ; STAT3 Transcription Factor/genetics* ; Resveratrol/pharmacology* ; Animals ; Janus Kinase 2/genetics* ; Signal Transduction/drug effects* ; Tumor Microenvironment/immunology* ; Cell Line, Tumor ; Mice, Inbred C57BL ; Mice ; Humans ; Cell Proliferation/drug effects* ; Bone Neoplasms/metabolism* ; CD8-Positive T-Lymphocytes/drug effects* ; Xenograft Model Antitumor Assays

Objective:To explore the clinical, imaging, and pathological features of glottic squamous cell carcinoma of the larynx and their relationship with prognosis. Methods:A retrospective analysis was conducted on the clinical, imaging, and pathological data of 130 patients with glottic squamous cell carcinoma of the larynx who were treated at the First People's Hospital of Yinchuan and the General Hospital of Ningxia Medical University from January 2018 to March 2023. Imaging examinations （CT and MRI） were used to evaluate the lesion boundary clarity, density, enhancement nature, and enhancement degree. Postoperative pathological examination was used to determine the pathological nature, immunohistochemistry, etc. Statistical methods such as χ² test, Spearman correlation analysis, multivariate logistic regression analysis, and Kaplan-Meier method were used to analyze the data. Results:Among the 130 patients, 127 were male and 3 were female, with an average age of （61.92±9.595） years. There was a correlation between clinical, imaging, and pathological features. Multivariate analysis showed that heterogeneous MRI density （OR=12.414;P=0.019） and squamous cell carcinoma as a subtype were correlated. The initial symptom of non-hoarseness （HR=6.045;P=0.010） and unclear MRI boundary （HR=12.559; P=0.029） were independent risk factors for poor prognosis in patients with glottic squamous cell carcinoma of the larynx. Conclusion:There is a correlation between the clinical, imaging, and pathological features of patients with glottic squamous cell carcinoma of the larynx, and they can affect prognosis. The initial symptom of non-hoarseness and unclear MRI boundary of the tumor are independent risk factors for poor prognosis.
Humans ; Laryngeal Neoplasms/diagnosis* ; Prognosis ; Male ; Female ; Retrospective Studies ; Middle Aged ; Carcinoma, Squamous Cell/diagnosis* ; Magnetic Resonance Imaging ; Glottis/pathology* ; Tomography, X-Ray Computed ; Aged

Objective:To investigate the clinical characteristics and major allergens of patients with pollen-food allergy syndrome（PFAS） and their correlation with the severity of symptoms, and to provide a basis for identifying high-risk patients, optimizing the allergen testing process and developing individualized dietary management strategies. Methods:The clinical data of 166 patients with PFAS admitted to our hospital from January 2021 to July 2023 were retrospectively analyzed. The clinical symptoms, pollen types and food allergy of the patients were analyzed by questionnaire survey and serum specific IgE detection. phi coefficient, Apriori algorithm modeling and multivariate logistic regression analysis were used to evaluate the association between allergen and symptom severity. Results:Artemisia pollen was the most common allergen in this area, with a positive rate of 96.39%. Peach and mango were the most common food allergens, which caused allergic reactions in 24.10% and 22.89% of patients, respectively. Oral mucosal symptoms were the main symptoms. Correlation analysis showed that there was a correlation between pollen allergens and allergenic food. Association rule analysis showed that when the patient was allergic to the combination of peanuts and trees, the probability of high severity of symptoms was 82.35%. Multivariate analysis showed that ragweed allergy was significantly positively correlated with the severity of PFAS symptoms. Conclusion:Artemisia pollen and related food allergens play an important role in the pathogenesis of PFAS. Association rule mining and network map analysis revealed direct associations between peanut and tree combination allergy and symptom severity, as well as potential links between other inhaled allergens and specific food allergies. Ragweed and peach allergy are independent risk factors for the aggravation of PFAS symptoms, which can be used as early warning indicators. These results help to improve the screening of high-risk patients and the construction of regional allergen databases.
Humans ; Food Hypersensitivity/immunology* ; Allergens/immunology* ; Retrospective Studies ; Pollen/immunology* ; Cross Reactions ; Immunoglobulin E/blood* ; Rhinitis, Allergic, Seasonal/immunology* ; Artemisia/immunology* ; Male ; Female ; Adult ; Prunus persica/immunology* ; Arachis/immunology* ; Middle Aged ; Surveys and Questionnaires ; Oral Allergy Syndrome

Objective:To explore the association between sublingual microcirculatory perfusion vessel proportion (PPV), high mobility group protein B1 (HMGB1), and sepsis-induced coagulopathy (SIC), and to identify early predictive markers for clinical intervention.Methods:A total of 66 septic patients admitted to the Respiratory Intensive Care Unit (RICU) between November 2021 and May 2024 were enrolled. Based on SIC diagnosis within 24 hours of admission, patients were categorized into SIC ( n=36) and non-SIC ( n=30) groups. Clinical parameters, including prothrombin time (PT), activated partial thromboplastin time (APTT), sublingual PPV, and serum HMGB1 levels (measured at 0 h and 6 h), were analyzed. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to identify independent predictors. Results:Compared with the non-SIC group, the SIC group demonstrated significantly prolonged PT ( P<0.05) and APTT ( P<0.05), elevated 0 h lactate levels, and increased 6 h HMGB1. Spearman analysis revealed a positive correlation between 6 h PPV and platelet count ( P<0.05), while an inverse correlation was observed with 6 h PT ( P<0.05). Multivariate regression identified APTT, 6 h PPV, and 6 h HMGB1 as independent predictors of SIC. ROC analysis yielded AUC values of 0.732 for APTT, 0.802 for 6 h PPV, and 0.765 for 6 h HMGB1. The combination of 6 h PPV and HMGB1 further improved predictive accuracy (AUC=0.873). Conclusions:Prolonged APTT, decreased 6 h PPV, and elevated 6h HMGB1 are key indicators of SIC. Integrated assessment of these markers enhances early risk stratification in septic patients, facilitating timely clinical intervention.

OBJECTIVE: To explore the implementation effect of hour-1 bundle for sepsis patients based on crisis resource management (CRM) system. METHODS: A historical control study was conducted. The hour-1 bundle for sepsis based on CRM was used to train 24 nurses in the emergency department from October 2022 to March 2023. Clinical data of sepsis patients admitted to the emergency department of the First People's Hospital of Zunyi from April 2022 to September 2023 were collected. The patients were divided into three groups based on different stages of CRM system construction: control group (before construction, from April to September in 2022), improvement group (during construction, from October 2022 to March 2023) and observation group (after construction, from April to September in 2023). The baseline data, implementation rate of hour-1 bundle [including blood culture, antibiotic usage, blood lactic acid (Lac) detection, fluid resuscitation, hypertensors usage], identification and diagnosis time, and prognosis parameters [including correction rate of hypoxemia, intensive care unit (ICU) occupancy rate, and 28-day survival rate]. Sepsis cognition survey and non-technical skill (NTS) evaluation of nurses in emergency department were conducted before and after training. RESULTS: Finally 43 cases were enrolled in the control group, improvement group and observation group, respectively. There was no statistically significant difference in baseline data including the gender, age, primary site, heart rate, systolic blood pressure, acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score, mechanical ventilation ratio among the three groups with comparability. With the gradual improvement of the CRM system, the implementation rate of 1-hour bundle was gradually increased, and the implementation rate in the control group, improvement group and observation group were 65.12% (28/43), 74.42% (32/43) and 88.37% (38/43), respectively, with statistically significant difference (P < 0.05). It was mainly reflected in the completion rate of blood culture, antibiotic usage rate, Lac detection rate and hypertensors usage rate within 1 hour, which were significantly higher in the observation group than those in the control group [completion rate of blood culture: 90.70% (39/43) vs. 62.79% (27/43), antibiotic usage rate: 88.37% (38/43) vs. 60.47% (26/43), Lac detection rate: 93.02% (40/43) vs. 72.09% (31/43), hypertensors usage rate: 88.37% (38/43) vs. 60.47% (26/43), all P < 0.05]. The fluid resuscitation rates within 1 hour in the three groups were all over 90%, with no statistically significant difference among the three groups. The recognition and diagnosis time in the observation group was significantly shorter than that in the control group and the improvement group (hours: 0.41±0.15 vs. 0.61±0.21, 0.51±0.18, both P < 0.05), the correction rate of hypoxemia and 28-day survival rate were significantly higher than those in the control group [correction rate of hypoxemia: 95.35% (41/43) vs. 74.42% (32/43), 28-day survival rate: 83.72% (36/43) vs. 60.47% (26/43), both P < 0.05], and ICU occupancy rate was significantly lower than that in the control group [72.09% (31/43) vs. 93.02% (40/43), P < 0.05]. After training in the CRM system, the score of the sepsis awareness survey questionnaire for emergency department nurses was significantly increased as compared with before training (60.42±5.29 vs. 44.17±9.21, P < 0.01), and NTS also showed significant improvement. CONCLUSION CRM plays a significant role in promoting the implementation of sepsis hour-1 bundle, which can improve the implementation rate of hour-1 bundle and NTS of medical staff, effectively improve patients' hypoxemia, reduce patients' ICU occupancy rate and 28-day risk of death.
Humans ; Sepsis/therapy* ; Emergency Service, Hospital ; Patient Care Bundles ; Intensive Care Units ; Female ; Male ; Middle Aged

This article reports a case of extensive ocular inflammation following zoledronic acid infusion for the treatment of osteoporosis. The patient developed pain, eyelid edema, conjunctival congestion, and decreased vision in the right eye one day after receiving intravenous zoledronic acid, and was diagnosed with uveitis, scleritis, and periorbital soft tissue inflammation. The patient′s symptoms were evaluated using the clinical activity score(CAS). After high-dose corticosteroid pulse therapy combined with other comprehensive treatments, the symptoms improved markedly. This article reviews the incidence, clinical features, potential mechanisms, management, and prognosis of ocular adverse reactions induced by zoledronic acid, and highlights the importance of early recognition and timely treatment of ocular inflammation after zoledronic acid therapy.

This article reports a case of extensive ocular inflammation following zoledronic acid infusion for the treatment of osteoporosis. The patient developed pain, eyelid edema, conjunctival congestion, and decreased vision in the right eye one day after receiving intravenous zoledronic acid, and was diagnosed with uveitis, scleritis, and periorbital soft tissue inflammation. The patient′s symptoms were evaluated using the clinical activity score(CAS). After high-dose corticosteroid pulse therapy combined with other comprehensive treatments, the symptoms improved markedly. This article reviews the incidence, clinical features, potential mechanisms, management, and prognosis of ocular adverse reactions induced by zoledronic acid, and highlights the importance of early recognition and timely treatment of ocular inflammation after zoledronic acid therapy.

Objective:Middle ear cholesteatoma is a common otolaryngological disease, and traditional diagnostic methods have certain limitations. This study aims to construct a computer-aided diagnosis model for middle ear cholesteatoma based on integrated convolutional neural networks (CNNs) to improve diagnostic accuracy and efficiency.Methods:Firstly, Data were collected from patients who visited the Department of Otorhinolaryngology Head and Neck Surgery at the First People′s Hospital of Yinchuan between January 2020 and December 2021. 8 000 temporal bone CT images were collected, including 5 000 images diagnosed pathologically as middle ear cholesteatoma and 3 000 normal images. A five-fold cross-validation method was used to divide the dataset into training and testing sets. Next, a transfer learning approach was used to initialize model parameters, and the AlexNet, GoogleNet, and ResNet networks were pre-trained to extract deep features from the images. Then, the Softmax classification algorithm was applied to classify the features, resulting in three independent classifiers. These classifiers were combined using an ensemble learning method with a weighted voting approach to obtain the final diagnostic results. Finally, the model was evaluated by comparing the ensemble classifier with individual classifiers to assess its accuracy, precision, sensitivity, specificity, and diagnostic time, and a comparison with low-mid-and high-experience physician groups was conducted to comprehensively evaluate the model′s diagnostic performance.Results:The experimental results showed that the model achieved an accuracy of 88.8%(178/200), precision of 92.9%,(112/120) sensitivity of 89.8%(108/120), and specificity of 88.1%(70/80). The average diagnostic time for individual patient temporal bone CT images was reduced to 2-3 seconds. Compared to the diagnostic results from low-mid-and high-experience physician groups, the model demonstrated significant advantages and effectively assisted clinicians in making rapid and accurate middle ear cholesteatoma diagnoses.Conclusion:The proposed middle ear cholesteatoma diagnostic model based on integrated convolutional neural networks exhibits high recognition accuracy and rapid diagnostic speed, significantly improving clinical diagnostic efficiency, especially in early screening and auxiliary diagnosis, making it of considerable value in clinical practice.

Objective:To screen differential proteins in the serum of workers with rare earth samarium oxide pneumoconiosis, in order to provide new ideas for finding its early diagnostic biomarkers.Methods:In April 2019, three male workers diagnosed with samarium oxide pneumoconiosis at a rare earth factory in Baotou City, Inner Mongolia Autonomous Region were selected as the observation group, and three male workers who were not exposed to dust were selected as the control group. The serum was sequenced using the Label-free proteomic method to screen for differentially expressed proteins, followed by cluster of orthologous groups of proteins (COG) annotation, gene ontology (GO) enrichment analysis, and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis. The interaction gene library retrieval tool database and Cytoscape 3.9.1 software were used to draw protein-protein interaction networks. CytoHubba plugin was used to screen for differentially expressed proteins with high scores, and real-time fluorescence quantitative polymerase chain reaction (RT/q-PCR) was used to validate the proteomic sequencing results.Results:A total of 45 up-regulated differentially expressed proteins and 5 down-regulated differentially expressed proteins were screened out in the serum of workers with rare earth samarium oxide pneumoconiosis. In the COG functional classification, post-translational modifications, protein turnover, and chaperones were the most numerous. GO enrichment included 25 entries for biological processes such as complement activation (classical pathways), 15 entries for cellular components such as extracellular recombinants, and 10 entries for molecular functions such as protein binding. The pathways identified by KEGG enrichment analysis mainly included infectious diseases, immune system, signal transduction, and immune related diseases. The top 10 scoring proteins were haptoglobin, complement C1r subcomponent, complement C1s subcomponent, apolipoprotein C-Ⅲ, apolipoprotein A-Ⅱ, prothrombin, afamin, complement component C8 gamma chain, complement component C6, complement component C7. The RT/q-PCR validation results showed that the mRNA expression levels of haptoglobin, prothrombin and complement C1s subcomponent in the observation group were significantly higher than those in the control group, and the differences were statistically significant ( P<0.05) . Conclusion:Ten differentially expressed proteins in the serum of workers with rare earth samarium oxide pneumoconiosis are screened, which provides a good idea for the screening of biomarkers for early diagnosis of samarium oxide pneumoconiosis.