Quick, simple and accurate diagnosis of suspected COVID-19 is very important for the screening and therapy of patients. Although several methods were performed in clinical practice, however, the IgM and IgG diagnostic value evaluation was little performed. 57 suspected COVID-19 infection patients were enrolled in our study. 24 patients with positive and 33 patients with negative nucleic acid test. The positive rate of COVID-19 nucleic acid was 42.10%. The positive detection rate of combination of IgM and IgG for patients with COVID-19 negative and positive nucleic acid test was 72.73% and 87.50%. The results were significantly higher than the nucleic acid or IgM, IgG single detection. hsCRP in the COVID-19 nucleic acid negative group showed significantly higher than the positive groups ( P =0.0298). AST in the COVID-19 IgM negative group showed significantly lower than the positive groups ( P =0.0365). We provided a quick, simple, accurate aided detection method for the suspected patients and on-site screening in close contact with the population.

Background: Pancreatic ductal adenocarcinoma (PDAC) is difficult to detect early and highly aggressive, often leading to poor patient prognosis. Existing serum biomarkers like CA19-9 are limited in early diagnosis, failing to meet clinical needs. Machine learning (ML)/deep learning (DL) technologies have shown great potential in biomedicine. This study aims to establish PDAC differential diagnosis and prognosis assessment models using ML combined with serum biomarkers for early diagnosis, risk stratification, and personalized treatment recommendations, improving early diagnosis rates and patient survival. Methods: The study included serum biomarker data and prognosis information from 117 PDAC patients. ML models (Random Forest (RF), Neural Network (NNET), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM)) were used for differential diagnosis, evaluated by accuracy, Kappa test, ROC curve, sensitivity, and specificity. COX proportional hazards model and DeepSurv DL model predicted survival risk, compared by C-index and Log-rank test. Based on DeepSurv’s risk predictions, personalized treatment recommendations were made and their effectiveness assessed. Results: Effective PDAC diagnosis and prognosis models were built using ML. The validation set data shows that the accuracy of the RF, NNET, SVM, and GBM models are 84.21%, 84.21%, 76.97%, and 83.55%; the sensitivity are 91.26%, 90.29%, 89.32%, and 88.35%; and the specificity are 69.39%, 71.43%, 51.02%, and 73.47%. The Kappa values are 0.6266, 0.6307, 0.4336, and 0.6215; and the AUC are 0.889, 0.8488, 0.8488, and 0.8704, respectively. BCAT1, AMY, and CA12-5 were selected as modeling parameters for the prognosis model using COX regression. DeepSurv outperformed the COX model on both training and validation sets, with C-indexes of 0.738 and 0.724, respectively. The Kaplan-Meier survival curves indicate that personalized treatment recommendations based on DeepSurv can help patients achieve survival benefits. Conclusion: This study built efficient PDAC diagnosis and prognosis models using ML, improving early diagnosis rates and prognosis accuracy. The DeepSurv model excelled in prognosis prediction and successfully guided personalized treatment recommendations and supporting PDAC clinical management.

Background: The second‐generation electrochemiluminescence immunoassay (ECLIA) kit of vitamin B12 is widely used in clinical laboratories, and the establishment of a reference interval (RI) is essential to provide the basis for clinical monitoring. The purpose of this study was to establish a laboratory RI for vitamin B12 in China and at the same time verify the method performance of the second‐generation kit. Methods: The verification of the method performance was conducted according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. Based on these guidelines, a total of 580 serum samples were collected, and 391 serum samples were used for the establishment of the RI according to CLSI guidelines. The subjects were grouped by sex and age. The age groups were as follows: 21‐40, 41‐60, and 61‐80 years. The RI was defined by nonparametric 2.5th and 97.5th percentile intervals. Results: The performance of the second‐generation kit of vitamin B12 from the Roche Cobas E602 system was in compliance with laboratory requirements. Serum vitamin B12 levels conformed to a non‐Gaussian distribution. Harris‐Boyd's test did not indicate partitioning for different age and gender group. Besides, there was no significant difference between different age groups ( P = .07) and gender groups ( P = .2002). The RI for healthy Chinese adults (aged 21‐80 years) calculated by the nonparametric method was 250.8‐957.1 pg/mL. Conclusions: The reference range of vitamin B12 was established, which provided a theoretical basis for the clinical application and monitoring of vitamin B12 detection.

BACKGROUND:Lung adenocarcinoma currently accounts for the highest cancer-related mortality rate worldwide. MiR-21-5p has a vital role in various types of cancers. We have analyzed the miR-21-5p expression level, prognosis, and associated molecular pathways in lung adenocarcinoma with multiple bioinformatics databases. MATERIAL AND METHODS:The Cancer Genome Atlas (TCGA) database was employed to fetch the miR-21-5p expression profile in multiple tumors. We used the UALCAN platform to assess the differential regulation of the miR-21-5p in healthy tissue and lung adenocarcinoma. Also, the survival prognosis of the miR-21-5p in each stage of lung adenocarcinoma was done by the Kaplan-Meier database. The STARBASE and UALCAN databases were employed to predict the miR-21-5p target genes, and the levels of target genes and their prognostic value were analyzed. RESULTS:MiR-21-5p was overexpressed in the majority of human cancers. MiR-21-5p demonstrated escalated expression in the lung adenocarcinoma tissue in contrast to the normal tissue (P<0.05). Poor prognosis was witnessed in the miR-21-5p high expression group as compared to the low expression group (hazard ratio [HR]= 1.59, P<0.05). PDZD2 was predicted as a miR-21-5p potential target. We found a negative correlation between PDZD2 and miR-21-5p (r=–0.255, P<0.05). PDZD2 was downregulated in lung adenocarcinoma (P<0.05). Overexpression of PDZD2 was associated with a better prognosis of survival in lung adenocarcinoma patients (HR=0.45, P<0.05). CONCLUSIONS:MiR-21-5p exhibits the potential to act as a biomarker for the survival prognosis of lung adenocarcinoma. It might be responsible for the onset and progression of lung adenocarcinoma through PDZD2 regulation.

Background: The purpose of this study was to investigate the clinical value of procalcitonin (PCT) and C-reactive protein (CRP) in the differential diagnosis of neonatal jaundice. Methods: Eighty-five cases of neonatal jaundice in our hospital from January 2016 to March 2019 were selected as research subjects, including 30 cases of physiological jaundice, 23 cases of infectious jaundice, and 32 cases of hemolytic jaundice. Five milliliters of non-anticoagulated venous peripheral blood and 3 mL EDTA-K+ anticoagulated venous peripheral blood were sampled from each newborn when the symptoms of jaundice occurred. The non-anticoagulated blood samples were then centrifuged at 3,500 rpm for 7 minutes and the serum was used for PCT and bilirubin examinations, and the anticoagulated blood samples were prepared for CRP examination. Receiver operating characteristic (ROC) curve analysis was performed for the evaluation of differential diagnosis of neonatal jaundice by PCT, CRP, and bilirubin levels. Results: Analyses of variance showed the postnatal age of jaundice occurring in the physiological jaundice group was older than those in the infectious jaundice and hemolytic jaundice groups (p < 0.001), and the PCT and CRP levels in the infectious jaundice group were higher than those in the hemolytic jaundice and physiological jaundice groups (p < 0.001). Pearson's correlation analysis indicated that the levels of PCT and CRP were negatively correlated with postnatal age in the physiological jaundice group (p < 0.05). ROC curve analysis demonstrated that PCT and CRP had the highest differential diagnosis efficacy of neonatal pathological and neonatal physiological jaundice with PCT and CRP at 0.70 mu g/L and 8.50 mg/L, respectively, as well as the highest differential diagnosis efficacy of neonatal infectious jaundice and neonatal hemolytic jaundice with PCT and CRP at 1.84 mu g/L and 13.50 mg/L, respectively. Conclusions: This study suggested that PCT and CRP possessed important clinical values in the differential diagnosis of neonatal jaundice, and PCT was superior to the differential diagnosis of neonatal infectious jaundice.