Objective To discuss the main pathological types and imaging characteristics of pulmonary nodules that are highly suspected to be malignant in clinical practice but are pathologically confirmed to be benign. Methods A retrospective analysis was performed on the clinical data of patients with pulmonary nodules who were initially highly suspected of malignancy but were subsequently pathologically confirmed to be benign. These patients were treated at the First Affiliated Hospital of Xiamen University from December 2020 to April 2023. Based on the outcomes of preoperative discussions, the patients were categorized into a benign group and a suspicious malignancy group. The clinical data and imaging characteristics of both groups were compared. Results A total of 232 patients were included in the study, comprising 112 males and 120 females, with a mean age of (50.7±12.0) years. Among these, 127 patients were classified into the benign group, while 105 patients were categorized into the suspicious malignancy group. No statistically significant differences were observed between the two groups regarding age, gender, symptoms, smoking history, or tumor history (P>0.05). However, significant differences were noted in nodule density, CT values, margins, shapes, and malignant signs (P＜0.05). Further analysis revealed that in the suspicious malignancy group, solid nodules were predominantly characterized by collagen nodules and fibrous tissue hyperplasia (33.3%), followed by tuberculosis (20.4%) and fungal infections (18.5%). In contrast, non-solid nodules were primarily composed of collagen nodules and fibrous tissue hyperplasia (41.2%) and atypical adenomatous hyperplasia (17.7%). Conclusion Benign pulmonary nodules that are suspected to be malignant are pathologically characterized by the presence of collagen nodules, fibrous tissue hyperplasia, tuberculosis, atypical adenomatous hyperplasia, and fungal infections. Radiologically, these nodules typically present as non-solid lesions and may exhibit features suggestive of malignancy, including spiculation, lobulation, cavitation, and pleural retraction.

This experiment was conducted to investigate the effects of agaric polysaccharides on an-tioxidant capacity,immune function,and intestinal flora of calves.Twenty-four healthy Holstein calves of(30±3)days of age and with the similar body weight at(55.33±1.86)kg were selected and randomly divided into two groups:the control group(group C)and test group(group T)with 12 replicates in each group and one calves in each replicate.Group C was fed starter and milk repla-cer,and group T was fed starter and milk replacer with 10 g of agaric polysaccharides to each calve for 10 d.Serum antioxidant,immune indexes and intestinal flora were tested.The results showed as follows:compared with group C,the enzyme activities of SOD and GSH-Px in serum of calves in group T were significantly increased(P＜0.05),and were increased by 29.09％and 15.35％,re-spectively;compared with group C,IgA,IL-2 and TNF-α were significantly increased in T group(P＜0.05).Adding agaric polysaccharides significantly increased the relative abundance of Firmi-cutes(P＜0.05)and decreased the relative abundance of Proteobacteria in feces of calf(P＞0.05);the relative abundance of Lactobalillus and Faecalibacterium were increased(P＜0.05);the relative abundance of Butyricoccus-pullicaecorum was increased(P＜0.05).LEfSe analysis results showed that there were 11 marker species in group T,such as Firmicutes and Lactobacillus,and 9 marker species in group C,such as Proteobacteria.The results showed that agaric polysaccharides could improve the antioxidant capacity and immune function of calves,and also could improve the structure of intestinal flora.

Objective To explore the value of preoperative detection of soluble fragments of cytokeratin-19 (CYFRA21-1), carcinoembryonic antigen (CEA), and postoperative detection of nuclear proliferation associated antigen Ki67 in prognostic evaluation of non-small cell lung cancer patients. Methods The clinicopathological data and follow-up results of patients with non-small cell lung cancer treated in the Department of Thoracic Surgery of the First Affiliated Hospital of Xiamen University in 2017 were collected. CYFRA21-1>3.39 ng/mL was defined as positive, and CEA>5 ng/mL was defined as positive. The receiver operating characteristic curve (ROC curve) of Ki67 expression level was drawn. The maximum area under the curve (AUC) was the cutoff value of Ki67 expression level, and the Ki67 expression level greater than its cutoff value was defined as positive. Cox regression analysis was used to determine the independent risk factors for poor prognosis in patients with non-small cell lung cancer. Results Finally 248 patients were collected, including 125 males and 123 females, with a median age of 61 years (ranging from 30 to 81 years) at the time of surgery. Univariate analysis showed that positive CYFRA21-1, high expression of Ki67, positive CEA, age≥60 years at operation, distant metastasis, lymph node metastasis, maximum tumor diameter>3 cm, and TNM stage Ⅲ were associated with poor prognosis in patients with non-small cell lung cancer. When combined detection of preoperative tumor markers and postoperative Ki67, the prognosis of all negative patients was the best, and that of all positive patients was the worst. Cox regression analysis showed that positive CEA+positive CYFRA21-1+high expression of Ki67 was an independent risk factor for poor prognosis in patients with non-small cell lung cancer (P<0.05). Conclusion The combined detection of preoperative serum CYFRA21-1, CEA, and postoperative Ki67 has important value in evaluating the prognosis of non-small cell lung cancer patients.

Following the rapid advancement of artificial intelligence technologies, especially the development of large language models like ChatGPT, the field of medical clinical practice is undergoing an unprecedented technological revolution. These advanced technologies, through efficient processing and analysis of large datasets, not only provide medical professionals with auxiliary diagnoses and treatment suggestions but also significantly enhance the quality and efficiency of medical education. This study conducts a comprehensive analysis and review of the applications of large language models in various aspects, including clinical inquiry, history collection, medical literature writing, clinical decision support, optimization of medical portal websites, patient health management, medical education, academic research, and scientific writing. However, the application of these technologies is not without flaws and presents several limitations and ethical challenges. This paper focuses on challenges related to technological errors, academic dishonesty, abuse risks, over-reliance, possibilities of misdiagnosis and treatment errors, and issues of accountability. In conclusion, large language models demonstrate tremendous potential in the integration and advancement of medical practices. Nevertheless, while fully harnessing the benefits brought by ChatGPT, it is essential to acknowledge and address these ethical challenges to ensure that the application of ChatGPT in the medical field is responsible and effective.

Objective:Laboratory evaluation of the relationship between cerebrospinal fluid and plasma indicators and intrathecal immunoglobulin G(IgG) synthesis in patients with neurological diseases, and establishment of a new diagnostic method for intrathecal IgG synthesis.Methods:This study retrospectively analyzed the content of IgG in cerebrospinal fluid samples and blood albumin in blood samples, and other test results of 410 patients with neurological diseases who visited Beijing Tiantan Hospital from 2019 to 2022. According to the results of oligoclonal bands in cerebrospinal fluid, patients were divided into intrathecal IgG synthesis group and non-intrathecal IgG synthesis group. The Mann Whitney U test was used for inter group comparison, and a bilateral test with P<0.05 indicates a statistically significant difference. Include indicators with differences between groups in logistic regression analysis, construct a predictive model, and compare it with the established quantitative formula IgG index. Results:There were significant differences in 10 indicators, including cerebrospinal fluid leukocyte count and 24-hour intrathecal IgG synthesis rate, between the intrathecal IgG synthesis group and the non-intrathecal IgG synthesis group, with P<0.05. The area under the curve (AUC) of intrathecal IgG synthesis was higher than the IgG index (AUC=0.920, 0.809, Z=31.178, P<0.001), the sensitivity was higher than the IgG index (0.825, 0.618), and the specificity was lower than the IgG index (0.876, 0.908). Conclusion:The combination of 10 indicators such as cerebrospinal fluid white blood cell count and 24-hour intrathecal IgG synthesis rate can improve the diagnostic efficacy and sensitivity of intrathecal IgG synthesis.

Single-molecule immunoassay technology represents an ultrasensitive immunoassay method that enables the resolution and detection of individual biomolecules at the nanoscale. This article highlights various representative techniques and clinical applications of single-molecule immunoassay technology, while also discussing the current challenges and future development directions. Through multiple optimizations at both the technical and commercial levels, single-molecule immunoassay technology exhibits unique advantages in real-time detection, disease diagnosis and treatment, and medical research. This technology is poised to contribute to the advancement of precision medicine by integrating individualized detection methods into clinical practice.

Objective:To establish and verify a diagnostic model for distinguishing multiple sclerosis (MS) from other neurological diseases with similar symptoms by usingcerebrospinal fluid oligoclonal band (CSF-OCB)combined with IgG intrathecal synthesis indicators and biochemical markers.Methods:Multiple sclerosis (MS) patients admitted to the Neurology Department of Beijing Tiantan Hospital affiliated with Capital Medical University from January 2014 to December 2022 were selected as the case group, while patients with similar neurological symptoms were selected as the control group. Using the case-control study design, a retrospective analysis was conducted on the detection of age, gender, oligoclonal bands in cerebrospinal fluid, IgG intrathecal synthesis indicators and biochemical indicators for all study subjects. The differential diagnosis model was determined by the multiple logistic regression analysis, and the receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficiency of the differential diagnosis model for neurological diseases with similar symptoms to MS and other conditions.Results:This study included 167 patients in the case group and 335 patients in the control group, of which 128 patients in the case group and 265 patients in the control group were used to construct the model, and 39 patients in the case group and 70 patients in the control group were used for model validation. The differential diagnostic model constructed by a multivariate logistic regression model was Y=0.871×CSF-OCB-0.051×CSFprotein-0.231×CSFchloride+1.183×gender-0.036×LDH+35.770. The model showed that the area under the curve, sensitivity and specificity were respectively 0.916, 87.3% and 87.6%. The Delong test results showed that the diagnostic efficacy of the model was significantly different from OCB, IgG intrathecal synthesis indicators, and OCB combined with IgG intrathecal synthesis indicators ( P<0.05). The new model validation showed that the actual diagnostic consistency rate for the MS group was 84.6%, while the actual diagnostic consistency rate for the control group was 90.0%. Conclusion:This study combines OCB, IgG intrathecal synthesis indicators, and biochemical indicators to establish a diagnostic prediction model for neurological diseases with similar clinical symptoms in MS. This model may have good differential diagnostic value and can better assist clinical diagnosis in the early stages of disease progression in MS patients.

Single-molecule immunoassay technology represents an ultrasensitive immunoassay method that enables the resolution and detection of individual biomolecules at the nanoscale. This article highlights various representative techniques and clinical applications of single-molecule immunoassay technology, while also discussing the current challenges and future development directions. Through multiple optimizations at both the technical and commercial levels, single-molecule immunoassay technology exhibits unique advantages in real-time detection, disease diagnosis and treatment, and medical research. This technology is poised to contribute to the advancement of precision medicine by integrating individualized detection methods into clinical practice.

Objective:To establish and verify a diagnostic model for distinguishing multiple sclerosis (MS) from other neurological diseases with similar symptoms by usingcerebrospinal fluid oligoclonal band (CSF-OCB)combined with IgG intrathecal synthesis indicators and biochemical markers.Methods:Multiple sclerosis (MS) patients admitted to the Neurology Department of Beijing Tiantan Hospital affiliated with Capital Medical University from January 2014 to December 2022 were selected as the case group, while patients with similar neurological symptoms were selected as the control group. Using the case-control study design, a retrospective analysis was conducted on the detection of age, gender, oligoclonal bands in cerebrospinal fluid, IgG intrathecal synthesis indicators and biochemical indicators for all study subjects. The differential diagnosis model was determined by the multiple logistic regression analysis, and the receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficiency of the differential diagnosis model for neurological diseases with similar symptoms to MS and other conditions.Results:This study included 167 patients in the case group and 335 patients in the control group, of which 128 patients in the case group and 265 patients in the control group were used to construct the model, and 39 patients in the case group and 70 patients in the control group were used for model validation. The differential diagnostic model constructed by a multivariate logistic regression model was Y=0.871×CSF-OCB-0.051×CSFprotein-0.231×CSFchloride+1.183×gender-0.036×LDH+35.770. The model showed that the area under the curve, sensitivity and specificity were respectively 0.916, 87.3% and 87.6%. The Delong test results showed that the diagnostic efficacy of the model was significantly different from OCB, IgG intrathecal synthesis indicators, and OCB combined with IgG intrathecal synthesis indicators ( P<0.05). The new model validation showed that the actual diagnostic consistency rate for the MS group was 84.6%, while the actual diagnostic consistency rate for the control group was 90.0%. Conclusion:This study combines OCB, IgG intrathecal synthesis indicators, and biochemical indicators to establish a diagnostic prediction model for neurological diseases with similar clinical symptoms in MS. This model may have good differential diagnostic value and can better assist clinical diagnosis in the early stages of disease progression in MS patients.

Objective To evaluate the value of intrathecal synthetic related markers in patients with mild cognitive impairment(MCI),Alzheimer's disease(AD),and other types of dementia.Methods Retrospec-tively collect the clinical data of 577 patients diagnosed with MCI(MCI group,178 cases),AD(AD group,131 cases),and other types of dementia(other types group,268 cases)from June 2019 to July 2023 in Beijing Tiantan Hospital,Capital Medical University.Oligoclonal zone electrophoresis(OCB)and 24 h intrathecal pro-tein synthesis rate(ISR)of each group were investigated,and the difference of different indexes among the groups was compared to evaluate the value of related indexes in the differential diagnosis of different diseases.Results Compared with AD group and other groups,AD group had a higher proportion of females,more patients were＞50-70 years old,and the incidence of abnormal lipid metabolism was higher,with statistical significance(P＜0.05).There were significant differences in OB(S),cerebrospinal fluid albumin,serum albumin and cerebrospinal flu-id IgG in different disease groups(P＜0.05).IgG index and ISR in patients with positive SOB(CSF)were higher than those in negative and weakly positive patients,and the differences were statistically significant(P＜0.001).IgG index was positively correlated with ISR(r=0.878,P＜0.001).Conclusion Intrathecal synthetic mark-ers such as IgG index,SOB(CSF)and 24 h ISR have synergistic effects in the diagnosis of cognitive dysfunction and various dementias,which can be collectively utilized in the diagnosis of diseases.