Dual-layer detector spectral CT-based machine learning models in the differential diagnosis of solitary pulmonary nodules.

The benign and malignant status of solitary pulmonary nodules (SPNs) is a key determinant of treatment decisions. The main objective of this study was to validate the efficacy of machine learning (ML) models featured with dual-layer detector spectral computed tomography (DLCT) parameters in identifying the benign and malignant status of SPNs. 250 patients with pathologically confirmed SPN were included in this study. 8 quantitative and 16 derived parameters were obtained based on the regions of interest of the lesions on the patients' DLCT chest enhancement images. 6 ML models were constructed from 10 parameters selected after combining the patients' clinical parameters, including gender, age, and smoking history. The logistic regression model showed the best diagnostic performance with an area under the receiver operating characteristic curve (AUC) of 0.812, accuracy of 0.813, sensitivity of 0.750 and specificity of 0.791 on the test set. The results suggest that the ML models based on DLCT parameters are superior to the traditional CT parameter models in identifying the benign and malignant nature of SPNs, and have greater potential for application.

Retrospective analysis of the clinical significance of Ro52/TRIM21 antibody and specific antinuclear antibody patterns by indirect immunofluorescence.

Objectives: To determine the clinical significance of Ro52 protein/tripartite motif-containing 21 antibody and specific antinuclear antibody patterns using indirect immunofluorescence technique. METHODS: The retrospective study was conducted at the clinical laboratory of the First Affiliated Hospital of Chongqing Medical University, China, and comprised data from January 2017 to December 2021 of patients who underwent antinuclear antibody and anti-extractable nuclear antigen antibody detection. Inpatients with Ro52 antibody-positive status were taken as the cases, while anti-Ro52 negative patients with clear clinical diagnosis were taken as the controls. Data was analysed using SPSS 19. RESULTS: There were 1802 cases and 1211 controls. Positive Ro52 showed significantly greater frequency in patients with primary Sjogren's syndrome, systemic lupus erythematosus, inflammatory myositis, dry eyes and interstitial lung disease (p<0.05). Ro52 antibody showed high positive predictive value for primary Sjogren's syndrome 25(96.15%), systemic lupus erythematosus 259(91.20%), connective tissue disease-associated interstitial lung disease 45(86.67%) and inflammatory myositis 60(86.67%). Antinuclear antibody indirect immunofluorescence patterns most frequently detected were nuclear speckled 128(40.89%) and cytoplasmic speckled 126(40.26%) (p<0.05). Interstitial lung disease was associated with the presence of cytoplasmic speckled antinuclear antibody indirect immunofluorescence pattern 24(19.2%), while tumours 47(36.5%) and hepatitis B 26(20.3%) seemed to be more frequent with nuclear speckled pattern (p<0.05). The simultaneous reactivity extractable nuclear antigen antibodies most frequently detected were antinuclear antibody+Ro52+anti-Sjogren's syndrome A+ 558(33.96%). CONCLUSIONS: Ro52 antibody positivity was found to be associated with Sjogren's syndrome, systemic lupus erythematosus, inflammatory myositis, dry eye and interstitial lung disease. The antinuclear antibody immunofluorescence pattern of Ro52 positive was single and primarily granular cytoplasm type. Antinuclear antibody negative and Ro52 positive in the serum of patients also had certain significance in auxiliary disease diagnosis.

Value of dual-layer spectral detector CT in predicting lymph node metastasis of non-small cell lung cancer.

Background: The accurate assessment of lymph node metastasis (LNM) is crucial for the staging, treatment, and prognosis of lung cancer. In this study, we explored the potential value of dual-layer spectral detector computed tomography (SDCT) quantitative parameters in the prediction of LNM in non-small cell lung cancer (NSCLC). Methods: In total, 91 patients presenting with solid solitary pulmonary nodules (8 mm < diameter ≤30 mm) with pathologically confirmed NSCLC (57 without LNM, and 34 with LNM) were enrolled in the study. The patients' basic clinical data and the SDCT morphological features were analyzed using the chi-square test or Fisher's exact test. The Mann-Whitney U-test and independent sample t-test were used to analyze the differences in multiple SDCT quantitative parameters between the non-LNM and LNM groups. The diagnostic efficacy of the corresponding parameters in predicting LNM in NSCLC was evaluated by plotting the receiver operating characteristic (ROC) curves. A multivariate logistic regression analysis was conducted to determine the independent predictive factors of LNM in NSCLC. Interobserver agreement was assessed using intraclass correlation coefficients (ICCs) and Bland-Altman plots. Results: There were no significant differences between the non-LNM and LNM groups in terms of age, sex, and smoking history. Lesion size and vascular convergence sign differed significantly between the two groups (P<0.05), but there were no significant differences in the six tumor markers. The SDCT quantitative parameters [SAR40keV, SAR70keV, Δ40keV, Δ70keV, CER40keV, CER70keV, NEF40keV, NEF70keV, λ, normalized iodine concentration (NIC) and NZeff] were significantly higher in the non-LNM group than the LNM group (P<0.05). The ROC analysis showed that CER40keV, NIC, and CER70keV had higher diagnostic efficacy than other quantitative parameters in predicting LNM [areas under the curve (AUCs) =0.794, 0.791, and 0.783, respectively]. The multivariate logistic regression analysis showed that size, λ, and NIC were independent predictive factors of LNM. The combination of size, λ, and NIC had the highest diagnostic efficacy (AUC =0.892). The interobserver repeatability of the SDCT quantitative and derived quantitative parameters in the study was good (ICC: 0.801-0.935). Conclusions: The SDCT quantitative parameters combined with the clinical data have potential value in predicting LNM in NSCLC. The size + λ + NIC combined parameter model could further improve the prediction efficacy of LNM.

Value of spectral computed tomography-derived quantitative parameters based on full volume analysis in the diagnosis of benign/malignant and pathological subtypes of solitary pulmonary nodules.

Background: Conventional dynamic computed tomography (CT) has a low specificity for the distinction between benign and malignant solitary pulmonary nodules (SPNs), and spectral CT has been proposed as a potential alternative. We aimed to investigate the role of quantitative parameters based on full-volume spectral CT in the differential diagnosis of SPNs. Methods: This retrospective study included spectral CT images of 100 patients with pathologically confirmed SPNs (78 and 22 in the malignant and benign groups, respectively). All cases were confirmed by postoperative pathology, percutaneous biopsy, and bronchoscopic biopsy. Multiple quantitative parameters derived from spectral CT were extracted from whole-tumor volume and standardized. Differences in quantitative parameters between groups were statistically analyzed. Diagnostic efficiency was evaluated by generating a receiver operating characteristic (ROC) curve. Between-group differences were evaluated using an independent sample t-test or Mann-Whitney U test. Interobserver repeatability was assessed using intraclass correlation coefficients (ICCs) and Bland-Altman plots. Results: Spectral CT-derived quantitative parameters, except attenuation difference between the SPN in the 70 keV and arterial enhancement [ΔS-A(70 keV)], were significantly higher for malignant SPNs than for benign nodules (P<0.05). In the subgroup analysis, most parameters could distinguish between the benign and adenocarcinoma groups, and between the benign and squamous cell carcinoma groups (P<0.05). Only 1 parameter could differentiate the adenocarcinoma and squamous cell carcinoma groups (P=0.020). ROC curve analysis indicated that normalized arterial enhancement fraction in the 70 keV (NEF70 keV), normalized iodine concentration (NIC), and Δ70 keV had high diagnostic efficacy for differentiating SPNs between the benign and malignant SPNs [area under the curve (AUC): 0.867, 0.866, and 0.848, respectively] and between the benign and adenocarcinoma groups (AUC: 0.873, 0.872, and 0.874, respectively). The multiparameters derived from spectral CT exhibited satisfactory interobserver repeatability (ICC: 0.856-0.996). Conclusions: Our study suggests that quantitative parameters derived from whole-volume spectral CT may be useful to improve discrimination of SPNs.

Value of dual-layer spectral detector computed tomography in the diagnosis of benign/malignant solid solitary pulmonary nodules and establishment of a prediction model.

Objective: This study aimed to investigate the role of spectral detector computed tomography (SDCT) quantitative parameters and their derived quantitative parameters combined with lesion morphological information in the differential diagnosis of solid SPNs. Methods: This retrospective study included basic clinical data and SDCT images of 132 patients with pathologically confirmed SPNs (102 and 30 patients in the malignant and benign groups, respectively). The morphological signs of SPNs were evaluated and the region of interest (ROI) was delineated from the lesion to extract and calculate the relevant SDCT quantitative parameters, and standardise the process. Differences in qualitative and quantitative parameters between the groups were statistically analysed. A receiver operating characteristic (ROC) curve was constructed to evaluate the efficacy of the corresponding parameters in the diagnosis of benign and malignant SPNs. Statistically significant clinical data, CT signs and SDCT quantitative parameters were analysed using multivariate logistic regression to determine the independent risk factors for predicting benign and malignant SPNs, and the best multi-parameter regression model was established. Inter-observer repeatability was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots. Results: Malignant SPNs differed from benign SPNs in terms of size, lesion morphology, short spicule sign, and vascular enrichment sign (P< 0.05). The SDCT quantitative parameters and their derived quantitative parameters of malignant SPNs (SAR40keV, SAR70keV, Δ40keV, Δ70keV, CER40keV, CER70keV, NEF40keV, NEF70keV, λ, NIC, NZeff) were significantly higher than those of benign SPNs (P< 0.05). In the subgroup analysis, most parameters could distinguish between benign and adenocarcinoma groups (SAR40keV, SAR70keV, Δ40keV, Δ70keV, CER40keV, CER70keV, NEF40keV, NEF70keV, λ, NIC, and NZeff), and between benign and squamous cell carcinoma groups (SAR40keV, SAR70keV, Δ40keV, Δ70keV, NEF40keV, NEF70keV, λ, and NIC). However, there were no significant differences between the parameters in the adenocarcinoma and squamous cell carcinoma groups. ROC curve analysis indicated that NIC, NEF70keV, and NEF40keV had higher diagnostic efficacy for differentiating benign and malignant SPNs (area under the curve [AUC]:0.869, 0.854, and 0.853, respectively), and NIC was the highest. Multivariate logistic regression analysis showed that size (OR=1.138, 95% CI 1.022-1.267, P=0.019), Δ70keV (OR=1.060, 95% CI 1.002-1.122, P=0.043), and NIC (OR=7.758, 95% CI 1.966-30.612, P=0.003) were independent risk factors for the prediction of benign and malignant SPNs. ROC curve analysis showed that the AUC of size, Δ70keV, NIC, and a combination of the three for differential diagnosis of benign and malignant SPNs were 0.636, 0.846, 0.869, and 0.903, respectively. The AUC for the combined parameters was the largest, and the sensitivity, specificity, and accuracy were 88.2%, 83.3% and 86.4%, respectively. The SDCT quantitative parameters and their derived quantitative parameters in this study exhibited satisfactory inter-observer repeatability (ICC: 0.811-0.997). Conclusion: SDCT quantitative parameters and their derivatives can be helpful in the differential diagnosis of benign and malignant solid SPNs. The quantitative parameter, NIC, is superior to the other relevant quantitative parameters and when NIC is combined with lesion size and Δ70keV value for comprehensive diagnosis, the efficacy could be further improved.

Long non-coding RNA MEG3 promotes tumor necrosis factor-alpha induced oxidative stress and apoptosis in interstitial cells of cajal via targeting the microRNA-21 /I-kappa-B-kinase beta axis.

Interstitial Cells of Cajal (ICC) plays a critical role in the peristaltic contractions of the gastrointestinal and urinary tract. The dysfunction and loss of ICC contributes to hypokinetic disease, such as gallstoneand ureteropelvic junction obstruction . In the present study, we identified the underlying driving molecular signals of oxidative stress and apoptosis in ICC. ICC was isolated from small intestine of Balb/c mice, and stimulated with tumor necrosis factor-alpha (TNF-α). MTT and flow cytometry were performed to assess cell viability, apoptosis, and the level of reactive oxygen species in ICC, respectively. The level of malondialdehyde, superoxide dismutase, and glutathione peroxidase in cells were measured to assess oxidative stress. The expression of inflammatory factors (interleukin, IL-1 and IL-6) and apoptosis-related proteins were detected by western blot. We observed that TNF-αinduced inflammation, oxidative stress and cell apoptosis in ICC. By using quantitative real-time PCR , we verified that the expression of long non-coding RNAMEG3 was elevated by TNF-α in ICC. Silencing MEG3 reversed inflammation, oxidative stress, and cell apoptosisin TNF-α-treated ICC. Subsequently, we confirmed that MEG3 sponged cytoprotective miR-21 to upregulate the expression of I-kappa-B-kinase beta (IKKB) and activate the nuclear factor kappa-B (NF-κB) pathway. Both miR-21 overexpression and IKKB knockdown reduced TNF-α-induced above symptoms in ICC. Taken together, we can conclude that MEG3 mediates inflammation, oxidative stress and apoptosis in TNF-α-treated ICC via the miR-21/IKKB-NF-κB axis. The study improves our understanding of the molecular mechanism of ICC reduction related diseases.

Rational design of a highly efficient catalytic system for the production of PAPS from ATP and its application in the synthesis of chondroitin sulfate.

The compound 3'-phosphoadenosine-5'-phosphosulfate (PAPS) serves as a sulfate group donor in the production of valuable sulfated compounds. However, elevated costs and low conversion efficiency limit the industrial applicability of PAPS. Here, we designed and constructed an efficient and controllable catalytic system for the conversion of adenosine triphosphate (ATP) (disodium salt) into PAPS without inhibition from by-products. In vitro and in vivo testing in Escherichia coli identified adenosine-5'-phosphosulfate kinase from Penicillium chrysogenum (PcAPSK) as the rate-limiting enzyme. Based on analysis of the catalytic steps and molecular dynamics simulations, a mechanism-guided "ADP expulsion" strategy was developed to generate an improved PcAPSK variant (L7), with a specific activity of 48.94 U·mg-1 and 73.27-fold higher catalytic efficiency (kcat/Km) that of the wild-type enzyme. The improvement was attained chiefly by reducing the ADP-binding affinity of PcAPSK, as well as by changing the enzyme's flexibility and lid structure to a more open conformation. By introducing PcAPSK L7 in an in vivo catalytic system, 73.59 mM (37.32 g·L-1 ) PAPS was produced from 150 mM ATP in 18.5 h using a 3-L bioreactor, and achieved titer is the highest reported to date and corresponds to a 98.13% conversion rate. Then, the PAPS catalytic system was combined with the chondroitin 4-sulfotransferase using a one-pot method. Finally, chondroitin sulfate was transformed from chondroitin at a conversion rate of 98.75%. This strategy has great potential for scale biosynthesis of PAPS and chondroitin sulfate.

Pichia nanzhaoensis sp. nov. and Pichia paraexigua f.a., sp. nov., two yeast species isolated from rotting wood.

Four yeast strains were isolated from rotting wood samples collected in the Baotianman Nature Reserve in Henan Province, Central China. On the basis of sequence analysis of the D1/D2 domains of the large subunit rRNA gene and the internal transcribed spacer regions, they were suggested to be two novel species of the genus Pichia. Pichia nanzhaoensis sp. nov. produces one to four spherical ascospores per ascus, and is most closely related to Candida pseudolambica. Pichia paraexigua f.a., sp. nov. is a sister taxa to Pichia exigua, but the formation of ascospores was not observed on various sporulation media. P. nanzhaoensis sp. nov. can weakly assimilate inulin, whereas P. paraexigua sp. nov. can weakly assimilate d-glucosamine. The type strain of Pichia nanzhaoensis is NYNU 178136T (=CICC 33279T=CBS 15346T) and the type strain of Pichia paraexigua is NYNU 178135T (=CICC 33278T=CBS 15237T).