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

Personalized drug response prediction from molecular data is an important challenge in precision medicine for treating cancer. Computational methods have been widely explored and have become increasingly accurate in recent years. However, the clinical application of prediction methods is still in its infancy due to large discrepancies between preclinial models and patients. We present a novel disentangled synthesis transfer network (DiSyn) for drug response prediction specifically designed for transfer learning from preclinical models to clinical patients. DiSyn uses a domain separation network (DSN) to disentangle drug response related features, employs data synthesis technology to increase the sample size and iteratively trains for better feature disentanglement. DiSyn is pretrained on large-scale unlabeled cancer samples and validated by three datasets, The Cancer Genome Atlas (TCGA), Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging And moLecular Analysis 2 (I-SPY2) and Novartis Institutes for Biomedical Research Patient-Derived Xenograft Encyclopedia (NIBR PDXE), achieving competitive performance with the state-of-the-art methods on cancer patients and mice. Furthermore, the application of DiSyn to thousands of breast cancer patients show the heterogeneity in drug responses and demonstrate its potential value in biomarker discovery and drug combination prediction.

Personalized drug response prediction from molecular data is an important challenge in precision medicine for treating cancer.Computational methods have been widely explored and have become increasingly accurate in recent years.However,the clinical application of prediction methods is still in its infancy due to large discrepancies between preclinial models and patients.We present a novel disentangled synthesis transfer network(DiSyn)for drug response prediction specifically designed for transfer learning from preclinical models to clinical patients.DiSyn uses a domain separation network(DSN)to disentangle drug response related features,employs data synthesis technology to increase the sample size and iteratively trains for better feature disentanglement.DiSyn is pretrained on large-scale unlabeled cancer samples and validated by three datasets,The Cancer Genome Atlas(TCGA),Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging And moLecular Analysis 2(I-SPY2)and Novartis Institutes for Biomedical Research Patient-Derived Xenograft Encyclopedia(NIBR PDXE),achieving competitive performance with the state-of-the-art methods on cancer patients and mice.Furthermore,the application of DiSyn to thousands of breast cancer patients show the heterogeneity in drug responses and demonstrate its potential value in biomarker discovery and drug combination prediction.

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: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.

Purpose To investigate the relationship between imaging characteristics and shunt grading in acute cerebral infarction patients with right-to-left shunt.Materials and Methods The clinical and imaging data of 697 acute cerebral infarction patients who were hospitalized in the Second Affiliated Hospital of Nanchang University from January 2019 to December 2021 were collected,and the patients were divided into right-to-left shunt negative group(443 cases)and right-to-left shunt positive group(254 cases)according bubble test,compared the difference in demographic data and imaging characteristics between the two groups.In the shunt positive group,the imaging characteristics of the two groups of patients and their relationship with the shunt grade were analyzed.Results There were no statistical differences in gender,age,smoking,hyperlipidemia and history of coronary heart disease between the two groups(P>0.05),but there were statistical differences in the history of hypertension(OR=0.533,95%CI 0.380-0.748),diabetes(OR=0.649,95%CI 0.422-0.999)and cerebral infarction(OR=0.275,95%CI 0.136-0.555)(all P<0.05).The imaging characteristics of the two groups of patients showed that there were significant differences in the number of infarct foci(χ2=53.957,4.219;both P<0.05),but there was no statistical difference in the infarct location between the two groups(P>0.05).Among the patients with acute cerebral infarction combined with positive bubble test,the imaging manifestations of grading I and II patients were mainly unilateral anterior circulation or posterior circulation infarction,and deep and single infarction were more common.In patients with grading III and IV shunts,multiple infarcts with combined bilateral anterior and posterior circulations were more common.Conclusion The imaging manifestations of patients with acute cerebral infarction combined with right-to-left shunt have their own characteristics.Bubble test has high sensitivity in the diagnosis of right-to-left shunt.The comprehensive analysis can provide certain guidance for clinical practice.

OBJECTIVE To analyze the clinicopathological features of laryngeal squamous carcinoma tumors and their correlation with prognosis in order to improve the understanding and diagnosis of laryngeal squamous cell carcinoma.METHODS The clinical and pathological data(including gender,age,stage,differentiation,immunohistochemistry,etc.)of 179 patients with laryngeal squamous cell carcinoma[171 males,8 females,aged 30-84(61.53±8.02)years]who were treated in Department of Otolaryngology Head and Neck Surgery,The First and Second Clinical Medical Schools of Ningxia Medical University from January 2015 to December 2022 were retrospectively studied,and the effects of various factors on prognosis were analyzed.RESULTS Among the 179 patients with laryngeal squamous cell carcinoma,the male-to-female ratio was 21.4:1,and the incidence was high in the age group of 60-79 years old(58.7%),and the youngest age of onset was 30 years old.The main clinical manifestations were hoarseness 138 cases(77.1%),sore throat 16 cases(8.9%)and pharyngeal foreign body sensation 13 cases(7.3%).Glottic type was more common in the primary site 135 cases(75.4%),and 31 cases were accompanied by cervical lymph node metastasis(17.3%).The degree of differentiation was more common in the moderately differentiated type 80 cases(44.7%).The positive rates of immunohistochemistry markers p16,EGFR(epidermal growth factor receptor),PD-1/PD-L1 and VEGF(vascular endothelial growth factor)were 20.3%,96.4%,36.4%and 77.3%,respectively.Univariate Kaplan-Meier survival analysis showed that the site of disease,lymph node metastasis,and tumor stage were significantly correlated with disease recurrence.Multivariate Cox regression analysis showed that the clinical stage of the tumor was an independent risk factor for the prognosis of the disease(HR=3.715,95%CI:1.519-9.088,P=0.04).CONCLUSION The stage of laryngeal squamous cell carcinoma,the site of the disease,and the metastasis of the lymph nodes are the main factors affecting the prognosis.The high positive expression rate of immunohistochemistry markers EGFR and VEGF is worth paying attention to Targeted therapy for patients with positive PD-1/PD-L1 testing is a promising research direction.

Objective:For tympanosclerosis patients with ossicular chain fixation, we use ossicular chain bypass technique and evaluate its long-term effects. Methods:From June 2017 to June 2019, 147 patients with tympanosclerosis who underwent middle ear surgery with otoscopy in Yinchuan First People's Hospital were reviewed. The subjects were divided into three groups according to the implemented operation plan, 51 cases in the ossicular chain mobilization group（OCM）, 56 cases in the ossicular chain bypass reconstruction group（OCB）, and 40 cases in the malleus-incus complex resection reconstruction group（MICR）. Through a three-year follow-up, the medium and long-term effects of different operation plans were compared and analyzed. Results:There was no significant difference among the three groups in the incidence of tympanic membrane perforation, delayed facial nerve palsy, and the dispatch and displacement of PORP. The incidence of tympanic membrane retraction pocket or cholesteatoma after operation in OCB group（0） was significantly lower than that in OCM group（11.76%） and MICR group（7.5%）（P<0.05）. At 12 months after operation, ΔABG of OCB group and MICR group were better than that in the OCM group（P<0.05）. At 36 months after operation, ΔABG of OCB group was better than that in the OCM group（P<0.05）, and there was no significant difference between OCB group and MICR group. The audiological performance of patients with epitympanic sclerosis（ETS） at 12, 24 and 36 months after operation was better than that of patients with posterior tympanosclerosis（PTS） and total tympanosclerosis（TTS）（P<0.05）. Conclusion:Compared with patients undergoing ossicular chain mobilization and malleus-incus complex resection for ossicular chain reconstruction, patients with tympanosclerosis undergoing bypass technique have better and stable hearing prognosis in medium and long term. This technique can effectively prevent the formation of retracted pocket and cholesteatoma in patients with tympanosclerosis after operation.
Humans ; Tympanosclerosis ; Ear Ossicles/surgery* ; Ear, Middle ; Malleus/surgery* ; Cholesteatoma ; Retrospective Studies ; Ossicular Prosthesis ; Treatment Outcome

Objective:To investigate the distribution of allergens in patients with allergic rhinitis （AR） in Ningxia, and provide theoretical data for the prevention and treatment of AR in this region. Methods:A total of 1664 patients diagnosed with AR in the Otorhinolaryngology Head and Neck Surgery Department of Yinchuan First People's Hospital Outpatient Clinic from January 2018 to December 2021 were retrospectively collected. Use the allergen sIgE antibody detection kit （immunoblotting method） to detect inhalation and ingestion allergens in patients.Results: ①Among all AR patients, 1 158 cases were detected positive, resulting in the detection rate was 69.59%; ②The detection rate of inhalation allergen was 65.87%, and the detection rate of ingestion allergen was 19.83%; ③Mugwort was the most sensitive allergen, and 76.32% of the patients having a positive grade ≥3; ④Out of the patients, 294 cases （25.39%） were allergic to only one allergen, 244 cases （21.07%） were allergic to two allergens, and 620 cases （53.54%） were allergic to three or more allergens; ⑤During different seasons, the highest number of positive allergens detected was in the summer, with 968 cases （83.59%）. Mugwort was the main allergen during this season （69.01%）. After the COVID-19 epidemic, the total positive rate of sIgE tests in AR patients decreased compared to before, and the difference was statistically significant （P<0.001）; ⑥Mugwort, dog epithelium, mold combination, egg, peanut, soybean, Marine fish combination and fruit combination all showed statistically significant differences between different gender groups （P<0.05）; ⑦Common ragweed, mugwort, dust mite combination, cockroach, egg, milk, Marine fish combination, shrimp, fruit combination and nut combination all showed statistically significant differences among different age groups （P<0.05）; ⑧There were statistically significant differences in hay dust among different ethnic groups （P<0.05）. Conclusion:Artemisia argyi is the main allergen in Ningxia, and the distribution characteristics of different allergens are influenced by treatment season, the COVID-19 epidemic, gender, age, ethnicity, and other factors, showing certain distribution patterns and rules.
Allergens ; Artemisia ; COVID-19 ; Retrospective Studies ; Rhinitis, Allergic ; Skin Tests ; Humans ; Male ; Female