OBJECTIVE: To explore the clinical characteristics and prognosis of multiple myeloma(MM) patients with secondary primary malignancies. METHODS: The clinical data of newly diagnosed MM patients admitted to the First Affiliated Hospital of Zhengzhou University from January 2011 to December 2019 were retrospectively analyzed. The patients with secondary primary malignancies were retrieved, and their clinical features and prognosis were evaluated. RESULTS: A total of 1 935 patients with newly diagnosed MM were admitted in this period, with a median age of 62 (18-94) years old, of which 1 049 cases were hospitalized twice or more. There were eleven cases with secondary primary malignancies (the incidence rate was 1.05%), including three cases of hematological malignancies (2 cases of acute myelomonocytic leukemia and 1 case of acute promyelocytic leukemia) and eight cases of solid tumors (2 cases of lung adenocarcinoma, and 1 case each of endometrial cancer, esophageal squamous cell carcinoma, primary liver cancer, bladder cancer, cervical squamous cell carcinoma, and meningioma). The median age of onset was 57 years old. The median time between diagnosis of secondary primary malignancies and diagnosis of MM was 39.4 months. There were seven cases with primary or secondary plasma cell leukemia, the incidence rate was 0.67%, and the median age of onset was 52 years old. Compared with the randomized control group, the β2-microglobulin level in the secondary primary malignancies group was lower (P=0.028), and more patients were in stage I/II of ISS (P=0.029). Among the 11 patients with secondary primary malignancies, one survived, ten died, and the median survival time was 40 months. The median survival time of MM patients after the secondary primary malignancies was only seven months. All seven patients with primary or secondary plasma cell leukemia died, with a median survival time of 14 months. The median overall survival time of MM patients with secondary primary malignancies was longer than that of the patients with plasma cell leukemia (P=0.027). CONCLUSION The incidence rate of MM with secondary primary malignancies is 1.05%. MM patients with secondary primary malignancies have poor prognosis and short median survival time, but the median survival time is longer than that of patients with plasma cell leukemia.
Humans ; Middle Aged ; Aged ; Aged, 80 and over ; Multiple Myeloma/complications* ; Leukemia, Plasma Cell ; Retrospective Studies ; Esophageal Neoplasms/complications* ; Esophageal Squamous Cell Carcinoma/complications* ; Prognosis ; Neoplasms, Second Primary

AIM: To analyze research hotspots and trends of artificial intelligence in diabetic retinopathy(DR)based on bibliometrics and high-impact papers.METHODS: Papers on artificial intelligence in DR research published in the Web of Science Core Collection(WoSCC)from January 1, 2012, to December 31, 2022 were retrieved. The data was analyzed by CiteSpace software to examine annual publication number, countries, institutions, source journal, research categories, keywords, and to perform an in-depth analysis of high-impact papers.RESULTS: A total of 1 009 papers on artificial intelligence in DR from 79 countries were included in the study, with 272 papers published in 2022. Notably, China and India contributed 287 and 234 papers, respectively. The United Kingdom exhibited a centrality score of 0.31, while the United States boasted an impressive H-index of 48. Three prominent institutions in the United Kingdom(University of London, Moorfields Eye Hospital, and University College London)and one institution in Egypt(Egyptian Knowledge Bank)all achieved a notable H-index of 14. The primary academic disciplines associated with this research field encompassed ophthalmology, computer science, and artificial intelligence. Burst keywords in the years 2021～2022 included transfer learning, vessel segmentation, and convolutional neural networks.CONCLUSION: China emerged as the leading contributor in terms of publication number in this field, while the United States stood out as a key player. Notably, Egyptian Knowledge Bank and University of London assumed leading roles among research institutions. Additionally, IEEE Access was identified as the most active journal within this domain. The research focus in the field of artificial intelligence in DR has transitioned from AI applications in disease detection and grading to a more concentrated exploration of AI-assisted diagnostic systems. Transfer learning, vessel segmentation, and convolutional neural networks hold substantial promise for widespread applications in this field.

Abstract： Objective　To analyze the value and influencing factors of cross-primer isothermal amplification technology(CPA) in clinical screening and diagnosis of tuberculosis (TB). Methods　We collected 543 inpatients in the Second Affiliated Hospital of Hainan Medical College from January 1, 2018 to December 31, 2021, including 179 patients with tuberculosis, 187 patients with pneumonia and 177 patients with other diseases. The patients' sputum, alveolar lavage fluid, pleural effusion and midstream urine were detected by CPA, smear microscopy, culture method and gene detection. The value of CPA detection in the diagnosis of tuberculosis and its influencing factors were evaluated. Statistical analysis was performed using SPSS 26.0. Results　The total positive rate of CPA was 14.4% (78/543), and the positive rate of sputum samples accounted for 29.1% (39/134). Among the 78 cases of CPA positive patients, the tuberculosis group accounted for 69.2% (54/78), followed by pneumonia group 21.8% (17/78), and other diseases group accounted for 9.0% (7/78). Taking CPA test as the reference method, the "sensitivity" of smear microscopy was lower than that of genetic testing and culture, while the "specificity" was higher than that of culture and gene testing, and the "missed diagnosis rate" of smear microscopy was higher than that of genetic testing and culture. CPA test positive was related to gender, ESR and pneumonia. There is a good agreement between CPA test and culture method and gene test (Kappa>0.9), and a moderate agreement between CPA test and smear microscopy (Kappa=0.616). Conclusions　Sputum specimen is the best choice for CPA detection, while the value of pleural effusion detection is relatively limited. Sputum, alveolar lavage fluid and midcourse urine can be used as clinical specimens for screening and diagnosis of "tuberculosis group and other disease group", while sputum can be used for screening and diagnosis of "tuberculosis group and pneumonia group". Gender, ESR and pneumonia are the influencing factors of CPA positive patients. Therefore, CPA testing is worthy of clinical promotion, but more clinical research data are needed.

Objective: To explore the efficacy of chemotherapy re-challenge in the third-line setting for patients with metastatic colorectal cancer (mCRC) in the real world. Methods: The clinicopathological data, treatment information, recent treatment efficacy, adverse events and survival data of mCRC patients who had disease progression after treatment with oxaliplatin-based and/or irinotecan-based chemotherapy and received third-line chemotherapy re-challenge from January 2013 to December 2020 at Tianjin Medical University Cancer Institute and Hospital were retrospectively collected. Survival curves were plotted with the Kaplan-Meier method, and the Cox proportional hazard model was used to analyze the prognostic factors. Results: A total of 95 mCRC patients were included. Among them, 32 patients (33.7%) received chemotherapy alone and 63 patients (66.3%) received chemotherapy combined with targeted drugs. Eighty-three patients were treated with dual-drug chemotherapy (87.4%), including oxaliplatin re-challenge in 35 patients and irinotecan re-challenge in 48 patients. The remaining 12 patients were treated with triplet chemotherapy regimens (12.6%). Among them, as 5 patients had sequential application of oxaliplatin and irinotecan in front-line treatments, their third-line therapy re-challenged both oxaliplatin and irinotecan; 7 patients only had oxaliplatin prescription before, and these patients re-challenged oxaliplatin in the third-line treatment. The overall response rate (ORR) and disease control rate (DCR) reached 8.6% (8/93) and 61.3% (57/93), respectively. The median progression free survival (mPFS) and median overall survival (mOS) were 4.9 months and 13.0 months, respectively. The most common adverse events were leukopenia (34.7%) and neutropenia (34.7%), followed by gastrointestinal adverse reactions such as nausea (32.6%) and vomiting (31.6%). Grade 3-4 adverse events were mostly hematological toxicity. Cox multivariate analysis showed that gender (HR=1.609, 95% CI: 1.016-2.548) and the PFS of front-line treatments (HR=0.598, 95% CI: 0.378-0.947) were independent prognostic factors. Conclusion: The results suggested that it is safe and effective for mCRC patients to choose third-line chemotherapy re-challenge, especially for patients with a PFS of more than one year in front-line treatments.
Humans ; Irinotecan/therapeutic use* ; Oxaliplatin/therapeutic use* ; Colorectal Neoplasms/pathology* ; Retrospective Studies ; Fluorouracil ; Colonic Neoplasms/chemically induced* ; Rectal Neoplasms/drug therapy* ; Antineoplastic Combined Chemotherapy Protocols/adverse effects* ; Camptothecin/adverse effects*

Objective: To explore the efficacy of chemotherapy re-challenge in the third-line setting for patients with metastatic colorectal cancer (mCRC) in the real world. Methods: The clinicopathological data, treatment information, recent treatment efficacy, adverse events and survival data of mCRC patients who had disease progression after treatment with oxaliplatin-based and/or irinotecan-based chemotherapy and received third-line chemotherapy re-challenge from January 2013 to December 2020 at Tianjin Medical University Cancer Institute and Hospital were retrospectively collected. Survival curves were plotted with the Kaplan-Meier method, and the Cox proportional hazard model was used to analyze the prognostic factors. Results: A total of 95 mCRC patients were included. Among them, 32 patients (33.7%) received chemotherapy alone and 63 patients (66.3%) received chemotherapy combined with targeted drugs. Eighty-three patients were treated with dual-drug chemotherapy (87.4%), including oxaliplatin re-challenge in 35 patients and irinotecan re-challenge in 48 patients. The remaining 12 patients were treated with triplet chemotherapy regimens (12.6%). Among them, as 5 patients had sequential application of oxaliplatin and irinotecan in front-line treatments, their third-line therapy re-challenged both oxaliplatin and irinotecan; 7 patients only had oxaliplatin prescription before, and these patients re-challenged oxaliplatin in the third-line treatment. The overall response rate (ORR) and disease control rate (DCR) reached 8.6% (8/93) and 61.3% (57/93), respectively. The median progression free survival (mPFS) and median overall survival (mOS) were 4.9 months and 13.0 months, respectively. The most common adverse events were leukopenia (34.7%) and neutropenia (34.7%), followed by gastrointestinal adverse reactions such as nausea (32.6%) and vomiting (31.6%). Grade 3-4 adverse events were mostly hematological toxicity. Cox multivariate analysis showed that gender (HR=1.609, 95% CI: 1.016-2.548) and the PFS of front-line treatments (HR=0.598, 95% CI: 0.378-0.947) were independent prognostic factors. Conclusion: The results suggested that it is safe and effective for mCRC patients to choose third-line chemotherapy re-challenge, especially for patients with a PFS of more than one year in front-line treatments.
Humans ; Irinotecan/therapeutic use* ; Oxaliplatin/therapeutic use* ; Colorectal Neoplasms/pathology* ; Retrospective Studies ; Fluorouracil ; Colonic Neoplasms/chemically induced* ; Rectal Neoplasms/drug therapy* ; Antineoplastic Combined Chemotherapy Protocols/adverse effects* ; Camptothecin/adverse effects*

Abstract: Objective　To analyze the etiological characteristics and drug resistance of patients with bloodstream infection (BSI) in the bacterial resistance monitoring network in Hainan Province from 2018 to 2020, so as to provide laboratory data for clinical diagnosis and treatment. Methods　The clinical data of the subjects were collected, and the etiological characteristics of BSI patients and drug resistance of commonly used drugs in clinical treatment were analyzed retrospectively. SPSS 26.0 software was used for statistical analysis. Results　A total of 877 strains were isolated, including Gram-negative bacteria (584 strains, 66.6%), Gram-positive bacteria (239 strains, 27.2%) and fungi (54 strains, 6.2%); male patients (591 cases, 67.4%), female patients (286 cases, 32.6%); inpatients (780 cases, 88.9%), outpatient and emergency patients (97 cases, 11.1%); the main primary diseases of BSI patients were hypertension, cerebral infarction and type 2 diabetes, and the main primary infections were pulmonary infection and urinary system infection. Intensive care unit (25.2%, 221 cases), emergency department (10.9%, 96 cases), oncology department (9.1%, 80 cases), nephrology department (6.8%, 60 cases) and hepatobiliary and pancreatic surgery department (4.3%, 38 cases) had the highest proportion of pathogenic bacteria. Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa, coagulase-negative Staphylococcus, Viridans group streptococci and Candida albicans were the most frequently isolated pathogens. The detection rates of carbapenem-resistant Klebsiella pneumoniae, carbapenem-resistant Pseudomonas aeruginosa and carbapenem-resistant Acinetobacter baumannii were 3.4%, 15.2% and 36.4% respectively. The carbapenem-resistant Escherichia coli was not checked out. The detection rates of methicillin resistant Staphylococcus aureus and methicillin resistant coagulase negative Staphylococcus were 18.5% and 79.1% respectively. Conclusions　Gram-negative bacteria are the most common pathogens of BSI, and inpatients are the main source of BSI. Age, underlying diseases and primary infection are the risk factors of BSI. Clinical laboratories should strengthen the etiological monitoring of high-risk patients with BSI, and the resistance analysis of common antibiotics can provide a basis for the rational use of antibiotics in clinical practice.

Objective:To study the effect of transcranial direct current stimulation (tDCS) regulating excitability of the vagus nerve on dysphagia after stroke. Methods:From September, 2020 to February, 2021, 28 patients with dysphagia after stroke were randomly divided into control group (n = 14) and tDCS group (n = 14). Both groups accepted swallowing function training, and tDCS group received anodal tDCS over vagus nerve, while the control group received sham tDCS. They were assessed with modified Mann Assessment of Swallowing Ability (MMASA) and Australian Therapy Outcome Measures (AusTOMs)-swallowing scale before and after treatment. Results:The scores of MMASA (|t| > 5.593, P < 0.001) and AusTOMs swallowing scale (|Z| > 2.121, P < 0.05) increased in both groups after treatment, and were higher in tDCS group than in the control group (|t| = 2.439, |Z| = 2.079, P < 0.05). Conclusion:Anodal tDCS over vagus nerve may further release dysphagia after stroke.

To make a preliminary pathological classification of lung adenocarcinoma with pure ground glass nodules(pGGN)on CT by using a deep learning model. CT images and pathological data of 219 patients(240 lesions in total)with pGGN on CT and pathologically confirmed adenocarcinoma were collected.According to pathological subtypes,the lesions were divided into non-invasive lung adenocarcinoma group(which included atypical adenomatous hyperplasia and adenocarcinoma in situ and micro-invasive adenocarcinoma)and invasive lung adenocarcinoma group.First,the lesions were outlined and labeled by two young radiologists,and then the labeled data were randomly divided into two datasets:the training set(80%)and the test set(20%).The prediction Results of deep learning were compared with those of two experienced radiologists by using the test dataset. The deep learning model achieved high performance in predicting the pathological types(non-invasive and invasive)of pGGN lung adenocarcinoma.The accuracy rate in pGGN diagnosis was 0.8330(95% =0.7016-0.9157)for of deep learning model,0.5000(95% =0.3639-0.6361)for expert 1,0.5625(95% =0.4227-0.6931)for expert 2,and 0.5417(95% =0.4029-0.6743)for both two experts.Thus,the accuracy of the deep learning model was significantly higher than those of the experienced radiologists(=0.002).The intra-observer agreements were good(Kappa values:0.939 and 0.799,respectively).The inter-observer agreement was general(Kappa value:0.667)(=0.000). The deep learning model showed better performance in predicting the pathological types of pGGN lung adenocarcinoma compared with experienced radiologists.
Adenocarcinoma of Lung ; Deep Learning ; Humans ; Lung Neoplasms ; Retrospective Studies ; Tomography, X-Ray Computed

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Increasing evidence suggests that a cyclic adenosine monophosphate (cAMP)-dependent intracellular signal drives the process of myelination. Yet, the signal transduction underlying the action of cAMP on central nervous system myelination remains undefined. In the present work, we sought to determine the role of EPAC (exchange protein activated by cAMP), a downstream effector of cAMP, in the development of the myelin sheath using EPAC1 and EPAC2 double-knockout (EPAC) mice. The results showed an age-dependent regulatory effect of EPAC1 and EPAC2 on myelin development, as their deficiency caused more myelin sheaths in postnatal early but not late adult mice. Knockout of EPAC promoted the proliferation of oligodendrocyte precursor cells and had diverse effects on myelin-related transcription factors, which in turn increased the expression of myelin-related proteins. These results indicate that EPAC proteins are negative regulators of myelination and may be promising targets for the treatment of myelin-related diseases.