[The timing of pericardial drainage catheter removal and restart of the anticoagulation in patients suffered from perioperative pericardial tamponade during atrial fibrillation catheter ablation and uninterrupted dabigatran: Experiences from 20 cases]

Objective: To investigate the timing of pericardial drainage catheter removal and restart of the anticoagulation in patients with atrial fibrillation (AF) suffered from perioperative pericardial tamponade during atrial fibrillation catheter ablation and uninterrupted dabigatran. Methods: A total of 20 patients with pericardial tamponade, who underwent AF catheter ablation with uninterrupted dabigatran in Beijing Anzhen Hospital from January 2019 to August 2021, were included in this retrospective analysis. The clinical characteristics of enrolled patients, information of catheter ablation procedures, pericardial tamponade management, perioperative complications, the timing of pericardial drainage catheter removal and restart of anticoagulation were analyzed. Results: All patients underwent pericardiocentesis and pericardial effusion drainage was successful in all patients. The average drainage volume was (427.8±527.4) ml. Seven cases were treated with idarucizumab, of which 1 patient received surgical repair. The average timing of pericardial drainage catheter removal and restart of anticoagulation in 19 patients without surgical repair was (1.4±0.7) and (0.8±0.4) days, respectively. No new bleeding, embolism and death were reported during hospitalization and within 30 days following hospital discharge. Time of removal of pericardial drainage catheter, restart of anticoagulation and hospital stay were similar between patients treated with idarucizumab or not. Conclusion: It is safe and reasonable to remove pericardial drainage catheter and restart anticoagulation as soon as possible during catheter ablation of atrial fibrillation with uninterrupted dabigatran independent of the idarucizumab use or not in case of confirmed hemostasis.

An ultra-small bispecific protein augments tumor penetration and treatment for pancreatic cancer

PURPOSE

The once highly anticipated antibody-based pathway-targeted therapies have not achieved promising outcomes for deadly pancreatic ductal adenocarcinoma (PDAC), mainly due to drugs' low intrinsic anticancer activity and poor penetration across the dense physiological barrier. This study aims to develop an ultra-small-sized, EGFR/VEGF bispecific therapeutic protein to largely penetrate deep tumor tissue and effectively inhibit PDAC tumor growth in vivo.

METHODS

The bispecific protein, Bi-fp50, was constructed by a typical synthetic biology method and labeled with fluorescent dyes for in vitro and in vivo imaging. Physicochemical properties, protein dual-binding affinity, and specificity of the Bi-fp50 were evaluated in several PDAC cell lines. In vitro quantitatively and qualitatively anticancer activity of Bi-fp50 was assessed by live/dead staining, MTT assay, and flow cytometry. In vivo pharmacokinetic and biodistribution were evaluated using blood biopsy samples and near-infrared fluorescence imaging. In vivo real-time tracking of Bi-fp50 in the local tumor was conducted by fibered confocal fluorescence microscopy. The subcutaneous PDAC tumor model was used to assess the in vivo antitumor effect of Bi-fp50.

RESULTS

Bi-fp50 with an ultra-small size of 50 kDa (5 ~ 6 nm) showed an excellent binding ability to VEGF and EGFR simultaneously and had enhanced, accumulated binding capability for Bxpc3 PDAC cells compared with anti-VEGF scFv and anti-EGFR scFv alone. Additionally, bi-fp50 significantly inhibited the proliferation and growth of Bxpc3 and Aspc1 PDAC cells even under a relatively low concentration (0.3 µM). It showed synergistically enhanced therapeutic effects relative to two individual scFv and Bi-fp50x control in vitro. The half-life of blood clearance of Bi-fp50 was 4.33 ± 0.23 h. After intravenous injection, Bi-fp50 gradually penetrated the deep tumor, widely distributed throughout the whole tissue, and primarily enriched in the tumor with nearly twice the accumulation than scFv2 in the orthotopic PDAC tumor model. Furthermore, the Bi-fp50 protein could induce broad apoptosis in the whole tumor and significantly inhibited tumor growth 3 weeks after injection in vivo without other noticeable side effects.

CONCLUSION

The proof-of-concept study demonstrated that the ultra-small-sized, bispecific protein Bi-fp50 could be a potential tumor suppressor and an efficient, safe theranostic tool for treating PDAC tumors.

Predicting PD-L1 expression status in patients with non-small cell lung cancer using [18F]FDG PET/CT radiomics

BACKGROUND

In recent years, immune checkpoint inhibitor (ICI) therapy has greatly changed the treatment prospects of patients with non-small cell lung cancer (NSCLC). Among the available ICI therapy strategies, programmed death-1 (PD-1)/programmed death ligand-1 (PD-L1) inhibitors are the most widely used worldwide. At present, immunohistochemistry (IHC) is the main method to detect PD-L1 expression levels in clinical practice. However, given that IHC is invasive and cannot reflect the expression of PD-L1 dynamically and in real time, it is of great clinical significance to develop a new noninvasive, accurate radiomics method to evaluate PD-L1 expression levels and predict and filter patients who will benefit from immunotherapy. Therefore, the aim of our study was to assess the predictive power of pretherapy [¹⁸F]-fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography/computed tomography (PET/CT)-based radiomics features for PD-L1 expression status in patients with NSCLC.

METHODS

A total of 334 patients with NSCLC who underwent [¹⁸F]FDG PET/CT imaging prior to treatment were analyzed retrospectively from September 2016 to July 2021. The LIFEx7.0.0 package was applied to extract 63 PET and 61 CT radiomics features. In the training group, the least absolute shrinkage and selection operator (LASSO) regression model was employed to select the most predictive radiomics features. We constructed and validated a radiomics model, clinical model and combined model. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to evaluate the predictive performance of the three models in the training group and validation group. In addition, a radiomics nomogram to predict PD-L1 expression status was established based on the optimal predictive model.

RESULTS

Patients were randomly assigned to a training group (n = 233) and a validation group (n = 101). Two radiomics features were selected to construct the radiomics signature model. Multivariate analysis showed that the clinical stage (odds ratio [OR] 1.579, 95% confidence interval [CI] 0.220-0.703, P < 0.001) was a significant predictor of different PD-L1 expression statuses. The AUC of the radiomics model was higher than that of the clinical model in the training group (0.706 vs. 0.638) and the validation group (0.761 vs. 0.640). The AUCs in the training group and validation group of the combined model were 0.718 and 0.769, respectively.

CONCLUSION

PET/CT-based radiomics features demonstrated strong potential in predicting PD-L1 expression status and thus could be used to preselect patients who may benefit from PD-1/PD-L1-based immunotherapy.

Metasurface-enhanced mid-infrared spectrochemical imaging of tissues

Label-free and nondestructive mid-infrared vibrational hyperspectral imaging is emerging as an important ex-vivo tissue analysis tool, providing spatially resolved biochemical information critical to understanding physiological and pathological processes. However, the chemically complex and spatially heterogeneous composition of tissue specimens and the inherently weak interaction of infrared light with biomolecules limit the analytical performance of infrared absorption spectroscopy. Here, we introduce an advanced mid-infrared spectrochemical tissue imaging modality using metasurfaces that support strong surface-localized electromagnetic fields to capture quantitative molecular maps of large-area murine brain-tissue sections. Our approach leverages polarization-multiplexed multi-resonance plasmonic metasurfaces to simultaneously detect many different functional biomolecules. The resulting surface-enhanced mid-infrared spectral imaging (SE-MIRSI) method eliminates the non-specific effects of bulk tissue morphology on the quantitative analysis of fingerprint spectra and improves the chemical selectivity. We show that the metasurface enhancement increases the retrieval of amide I and II absorption bands associated with secondary structures of proteins. Moreover, we demonstrate that plasmonic metasurfaces enhance the chemical contrast in infrared images and enable the detection of ultrathin tissue regions that are not otherwise visible to conventional mid-infrared spectral imaging. While we tested our approach on murine brain tissue sections, this chemical imaging method is well-suited for any tissue type, which significantly broadens the potential impacts of our method for both translational research and clinical histopathology.

Tuberculosis complicated by spinal cord cryptococcosis: a case report and literature review

BACKGROUND

Spinal cord involvement by Cryptococcus neoformans infection is extremely rare, with most cases occurring in immunosuppressed patients.

CASE PRESENTATION

A young male patient presented with a 10-day history of progressive lower limb weakness culminating in paralysis, urinary incontinence, and constipation. The patient had no known immunodeficiency induced by the human immunodeficiency virus (HIV), malignancy, or organ transplantation. Laboratory investigations showed elevated C-reactive protein (CRP) levels; however, all other immune indicators were normal. Magnetic resonance imaging (MRI) revealed oval-shaped extradural masses (1.3-3.5 cm) with isointense T1-weighted signal and heterogeneous T2-weighted signal in the spinal canal at the level of the 9th thoracic vertebra. The lesions spread along the intervertebral foramen and involved both sides, showing significant enhancement in contrast-enhanced MRI. The patient was managed surgically, in combination with antifungal and anti-tuberculous therapy and could walk independently 3 months after the treatment. Cryptococcosis was confirmed by histopathology and fungal culture.

CONCLUSIONS

The results suggest that for lesions that affect spinal stability or cause severe nerve damage, surgical treatment should be considered along with medical management.

18F-labeled FGFR1 peptide: a new PET probe for subtype FGFR1 receptor imaging

Introduction

The fibroblast growth factor receptor (FGFR) family is highly expressed in a variety of tumor types and represents a new target for cancer therapy. Different FGFR subtype aberrations have been found to exhibit highly variable sensitivity and efficacy to FGFR inhibitors.

Methods

The present study is the first to suggest an imaging method for assessing FGFR1 expression. The FGFR1-targeting peptide NOTA-PEG2-KAEWKSLGEEAWHSK was synthesized by manual solid-phase peptide synthesis and high-pressure liquid chromatography (HPLC) purification and then labeled with fluorine-18 using NOTA as a chelator. In vitro and in vivo experiments were conducted to evaluate the stability, affinity and specificity of the probe. Tumor targeting efficacy and biodistribution were evaluated by micro-PET/CT imaging in RT-112, A549, SNU-16 and Calu-3 xenografts.

Results

The radiochemical purity of [18F]F-FGFR1 was 98.66% ± 0.30% (n = 3) with excellent stability. The cellular uptake rate of [18F]F-FGFR1 in the RT-112 cell line (FGFR1 overexpression) was higher than that in the other cell lines and could be blocked by the presence of excess unlabeled FGFR1 peptide. Micro-PET/CT imaging revealed a significant concentration of [18F]F-FGFR1 in RT-112 xenografts with no or very low uptake in nontargeted organs and tissues, which demonstrated that [18F]F-FGFR1 was selectively taken up by FGFR1-positive tumors.

Conclusion

[18F]F-FGFR1 showed high stability, affinity, specificity and good imaging capacity for FGFR1-overexpressing tumors in vivo, which provides new application potential in the visualization of FGFR1 expression in solid tumors.

Combined CT and serum CA19-9 for stratifying risk for progression in patients with locally advanced pancreatic cancer receiving intraoperative radiotherapy

Background and purpose

The aim of this study was to evaluate the significance of baseline computed tomography (CT) imaging features and carbohydrate antigen 19-9 (CA19-9) in predicting prognosis of locally advanced pancreatic cancer (LAPC) receiving intraoperative radiotherapy (IORT) and to establish a progression risk nomogram that helps to identify the potential beneficiary of IORT.

Methods

A total of 88 LAPC patients with IORT as their initial treatment were enrolled retrospectively. Clinical data and CT imaging features were analyzed. Cox regression analyses were performed to identify the independent risk factors for progression-free survival (PFS) and to establish a nomogram. A risk-score was calculated by the coefficients of the regression model to stratify the risk of progression.

Results

Multivariate analyses revealed that relative enhanced value in portal-venous phase (REV-PVP), peripancreatic fat infiltration, necrosis, and CA19-9 were significantly associated with PFS (all p < 0.05). The nomogram was constructed according to the above variables and showed a good performance in predicting the risk of progression with a concordance index (C-index) of 0.779. Our nomogram stratified patients with LAPC into low- and high-risk groups with distinct differences in progression after IORT (p < 0.001).

Conclusion

The integrated nomogram would help clinicians to identify appropriate patients who might benefit from IORT before treatment and to adapt an individualized treatment strategy.

Muscle Fat Content Is Associated with Nonalcoholic Fatty Liver Disease and Liver Fibrosis in Chinese Adults

OBJECTIVES

Several studies have linked myosteatosis with nonalcoholic fatty liver disease (NAFLD) in individuals with obesity. The clinical significance of myosteatosis in individuals with NAFLD in the general population has not been well investigated. Here, we wanted to explore and compare the associations of NAFLD and liver fibrosis with muscle fat content and skeletal muscle mass (SMM) in a relatively large general population in China.

METHODS

We retrospectively included all participants who underwent abdominal CT scans in our health promotion center between April 2021 and October 2021. Muscle fat content was assessed by abdomen quantitative computed tomography (QCT) scans, and SMM was evaluated by bioelectrical impedance. NAFLD was assessed by ultrasonography. The NAFLD fibrosis score (NFS) and Fibrosis-4 Index (FIB-4) score were calculated to assess liver fibrosis.

RESULTS

Compared with participants without NAFLD, patients with NAFLD showed significantly increased intermuscular adipose tissue (IMAT%) (7.40±3.37% vs. 6.76±2.66%, P <0.01). According to a multiple logistic regression model, IMAT% (OR=1.091, 95% CI 1.030-1.155, P=0.003) was only independently correlated with NAFLD in obese participants. Mediation analysis showed that BMI mediated the association between IMAT% and NAFLD. In participants with NAFLD, increased IMAT% was independently associated with an increased intermediate to high risk of advanced fibrosis assessed by the NFS or FIB-4 score after adjusting for multiple potential confounders. However, SMM was only independently correlated with an intermediate to high risk for advanced fibrosis evaluated by the NFS and not by the FIB-4 score.

CONCLUSION

Increased muscle fat content is positively correlated with NAFLD and intermediate to high risk for advanced fibrosis in the general Chinese population.

[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs]

Objective: To develop and validate a deep learning model based on fundus photos for the identification of coronary heart disease (CHD) and associated risk factors. Methods: Subjects aged>18 years with complete clinical examination data from 149 hospitals and medical examination centers in China were included in this retrospective study. Two radiologists, who were not aware of the study design, independently evaluated the coronary angiography images of each subject to make CHD diagnosis. A deep learning model using convolutional neural networks (CNN) was used to label the fundus images according to the presence or absence of CHD, and the model was proportionally divided into training and test sets for model training. The prediction performance of the model was evaluated in the test set using monocular and binocular fundus images respectively. Prediction efficacy of the algorithm for cardiovascular risk factors (e.g., age, systolic blood pressure, gender) and coronary events were evaluated by regression analysis using the area under the receiver operating characteristic curve (AUC) and R² correlation coefficient. Results: The study retrospectively collected 51 765 fundus images from 25 222 subjects, including 10 255 patients with CHD, and there were 14 419 male subjects in this cohort. Of these, 46 603 fundus images from 22 701 subjects were included in the training set and 5 162 fundus images from 2 521 subjects were included in the test set. In the test set, the deep learning model could accurately predict patients' age with an R² value of 0.931 (95%CI 0.929-0.933) for monocular photos and 0.938 (95%CI 0.936-0.940) for binocular photos. The AUC values for sex identification from single eye and binocular retinal fundus images were 0.983 (95%CI 0.982-0.984) and 0.988 (95%CI 0.987-0.989), respectively. The AUC value of the model was 0.876 (95%CI 0.874-0.877) with either monocular fundus photographs and AUC value was 0.885 (95%CI 0.884-0.888) with binocular fundus photographs to predict CHD, the sensitivity of the model was 0.894 and specificity was 0.755 with accuracy of 0.714 using binocular fundus photographs for the prediction of CHD. Conclusion: The deep learning model based on fundus photographs performs well in identifying coronary heart disease and assessing related risk factors such as age and sex.

The reduction of 18F-FDG uptake ability of tumor tissue after neoadjuvant chemoradiotherapy in locally advanced rectal cancer can effectively reflect the degree of tumor regression

Introduction

To evaluate the predictive value of ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET-CT) imaging parameters for the response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC).

Methods

From January 2016 to March 2020, 52 LARC patients who underwent ¹⁸F-FDG PET-CT scans within 1 week before and 8-9 weeks after nCRT, were enrolled in this study according to a pre-designed screening criteria. After total mesorectal excision (TME) surgery, we assessed tumor response to treatment and analyzed the correlation between imaging parameters obtained from two PET-CT scans and tumor regression status.

Results

Tumor response assessment showed that 13 of 52 patients received good response (GR), including 9 cases with pathological complete regression (pCR) and 4 cases with near-pathological complete regression (near-pCR). We also found that the maximum standard uptake value after nCRT (post-SUVmax), the response index (RI), the mean standard uptake values after nCRT (post-SUVmean), and the ratio of tumor SUVmean to liver SUVmean after nCRT (post-Ratio), were correlated with GR and pCR. Among these parameters, post-SUVmax and RI had a near-strong correlation with pCR (r_s= -0.58 and 0.59, respectively), and also had a strong correlation with GR (r_s = -0.7 and 0.63, respectively). Further ROC analysis showed that post-SUVmax and RI had higher values in predicting whether patients could achieve GR and pCR after nCRT, and the area under the curve (AUC) of both were greater than 0.9. The positive predictive values (PPVs) and negative predictive values (NPVs) of post-SUVmax for GR were 80.01% and 97.3%, and for pCR were 66.68% and 97.5%, respectively. The PPVs and NPVs of the RI values for GR were 84.61% and 94.87%, and for pCR were 69.24% and 100%, respectively.

Conclusion

For LARC patients, the analysis of imaging parameters such as post-SUVmax and RI, which can reflect the changes of ¹⁸F-FDG uptake capacity of tumor tissues before and after nCRT, is of great value for predicting the response of patients to neoadjuvant therapy and guiding the selection of subsequent treatment strategies.

Added value of histogram analysis of ADC in predicting radiation-induced temporal lobe injury of patients with nasopharyngeal carcinoma treated by intensity-modulated radiotherapy

BACKGROUND

This study evaluated the predictive potential of histogram analysis derived from apparent diffusion coefficient (ADC) maps in radiation-induced temporal lobe injury (RTLI) of nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT).

RESULTS

Pretreatment diffusion-weighted imaging (DWI) of the temporal lobes of 214 patients with NPC was retrospectively analyzed to obtain ADC histogram parameters. Of the 18 histogram parameters derived from ADC maps, 7 statistically significant variables in the univariate analysis were included in the multivariate logistic regression analysis. The final best prediction model selected by backward stepwise elimination with Akaike information criteria as the stopping rule included kurtosis, maximum energy, range, and total energy. A Rad-score was established by combining the four variables, and it provided areas under the curve (AUCs) of 0.95 (95% confidence interval [CI] 0.91-0.98) and 0.89 (95% CI 0.81-0.97) in the training and validation cohorts, respectively. The combined model, integrating the Rad-score with the T stage (p = 0.02), showed a favorable prediction performance in the training and validation cohorts (AUC = 0.96 and 0.87, respectively). The calibration curves showed a good agreement between the predicted and actual RTLI occurrences.

CONCLUSIONS

Pretreatment histogram analysis of ADC maps and their combination with the T stage showed a satisfactory ability to predict RTLI in NPC after IMRT.

Genetic influences of the effect of circulating inflammatory cytokines on osteoarthritis in humans

OBJECTIVE

The causal relationship between inflammatory cytokines and Osteoarthritis (OA) has not been well investigated. This study investigated the causal role of inflammatory cytokines in the risk of OA and total joint arthroplasty using the Mendelian randomization (MR) method.

METHOD

Single nucleotide polymorphisms (SNPs) robustly associated with inflammatory cytokines were used as instrumental variables. The inverse-variance weighted (IVW) method with false discovery rate (FDR) adjusted P-value (q-value) for multiple comparisons were used as the main MR method to estimate causal effects based on the summary-level data for OA (knee and hip OA, respectively) and total joint arthroplasty (TJA). Sensitivity analyses validated the robustness of the results and ensured the absence of heterogeneity and horizontal pleiotropy.

RESULTS

After FDR adjustment, macrophage colony-stimulating factor (MCSF) and vascular endothelial growth factor (VEGF) were identified as causally associated with knee OA (MCSF, odds ratio [OR]: 1.16, 95% confidence interval [CI]: 1.09-1.23, q = 5.05 × 10^-5; VEGF, OR: 1.09, 95% CI: 1.04-1.15, q = 0.011). We also observed that genetically predicted MCSF and VEGF were positively associated with the risk of TJA, and MCP3 was negatively associated with for the risk of TJA, although the effects seem fairly modest. Sensitivity analysis further excluded the influence of heterogeneity and horizontal pleiotropy.

CONCLUSIONS

Inflammatory cytokines, namely MCSF and VEGF, were causally associated with knee OA, which could enhance our understanding of inflammation in OA pathology.

Comprehensive analysis of pre-mRNA alternative splicing regulated by m6A methylation in pig oxidative and glycolytic skeletal muscles

BACKGROUND

Different types of skeletal myofibers exhibit distinct physiological and metabolic properties that are associated with meat quality traits in livestock. Alternative splicing (AS) of pre-mRNA can generate multiple transcripts from an individual gene by differential selection of splice sites. N6-methyladenosine (m6A) is the most abundant modification in mRNAs, but its regulation for AS in different muscles remains unknown.  RESULTS: We characterized AS events and m6A methylation pattern in pig oxidative and glycolytic muscles. A tota1 of 1294 differential AS events were identified, and differentially spliced genes were significantly enriched in processes related to different phenotypes between oxidative and glycolytic muscles. We constructed the regulatory network between splicing factors and corresponding differential AS events and identified NOVA1 and KHDRBS2 as key splicing factors. AS event was enriched in m6A-modified genes, and the methylation level was positively correlated with the number of AS events in genes. The dynamic change in m6A enrichment was associated with 115 differentially skipping exon (SE-DAS) events within 92 genes involving in various processes, including muscle contraction and myofibril assembly. We obtained 23.4% SE-DAS events (27/115) regulated by METTL3-meditaed m6A and experimentally validated the aberrant splicing of ZNF280D, PHE4DIP, and NEB. The inhibition of m6A methyltransferase METTL3 could induce the conversion of oxidative fiber to glycolytic fiber in PSCs.

CONCLUSION

Our study suggested that m6A modification could contribute to significant difference in phenotypes between oxidative and glycolytic muscles by mediating the regulation of AS. These findings would provide novel insights into mechanisms underlying muscle fiber conversion.

Genome-wide association study for reproduction-related traits in Chinese domestic goose

1. This study measured six reproduction traits in a Sichuan white goose population (209 individuals), including fertility, qualified egg rate, plasma concentrations of progesterone (P), follicle-stimulating hormone (FSH), prolactin (PRL) and oestrogen (E2).2. Whole-genome resequencing data from the same goose population (209 individuals) were used in a genome-wide association study (GWAS) utilising a mixed linear model to investigate the genes and genetic markers associated with reproduction traits. The frequency of the selected SNPs and haplotypes were determined using the Matrix-Assisted Laser Desorption Ionisation Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) method.3. In total, 42 SNPs significantly associated with these traits were identified. A haplotype block was constructed based on five SNPs that were significantly associated with qualified egg rate, with individuals having the haplotype CCTTAAGGAA having the lowest qualified egg rate.4. In conclusion, these results provided potential markers for marker-assisted selection to improve goose reproductive performance and a basis for elucidating the genetics of goose reproduction.

Development and validation of a prediction model of pneumothorax after CT-guided coaxial core needle lung biopsy

BACKGROUND

Pneumothorax is the most common complication of computed tomography-guided coaxial core needle biopsy (CCNB) and may be life-threatening. We aimed to evaluate the risk factors and develop a model for predicting pneumothorax in patients undergoing computed tomography-guided CCNB, and to further determine its clinical utility.

METHODS

Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for pneumothorax from 18 variables. A predictive model was established using multivariable logistic regression and presented as a nomogram based on a training cohort of 690 patients who underwent computed tomography-guided CCNB. The model was validated in 253 consecutive patients in the validation cohort and 250 patients in the test cohort. The area under the curve was used to determine the predictive accuracy of the proposed model.

RESULTS

The risk factors associated with pneumothorax after computed tomography-guided CCNB were sex, patient position, lung field, lesion contact with the pleura, lesion size, distance from the pleura to the lesion, presence of emphysema adjacent to the biopsy tract, and crossing fissures. The predictive model that incorporated these predictors showed good predictive performance in the training cohort [area under the curve, 0.71 (95% confidence interval: 0.67-0.75)], validation cohort [0.71 (0.64-0.78)], and internal test cohort [0.68 (0.60-0.75)]. The nomogram also provided excellent calibration and discrimination, and decision curve analysis (DCA) demonstrated its clinical utility.

CONCLUSIONS

The predictive model showed good performance for pneumothorax after computed tomography-guided CCNB and may help improve individualized preoperative prediction.

[Distribution and gene characteristics of H3, H4 and H6 subtypes of low pathogenic avian influenza viruses in environment related avian influenza viruses during 2014-2021 in China]

Objective: To analyze the characteristics of low pathogenic H3, H4 and H6 subtypes of avian influenza viruses in environment related avian influenza viruses in China from 2014 to 2021. Methods: Surveillance sites were located in 31 provinces, autonomous region and municipalities to collect environmental samples related to avian influenza, detect the nucleic acid detection of influenza A virus, isolate virus, deeply sequence, analyze pathogenicity related molecular sites, and determine the distribution and variation characteristics of common H3, H4 and H6 subtypes of avian influenza virus in different regions, places and sample types. Results: A total of 388 645 samples were collected. The positive rate of low pathogenic H3 (0.56‰) and H6 (0.53‰) was higher than that of H4 (0.09‰). The positive rate of H4 subtype virus in live poultry market was higher than that in other places, and the difference was statistically significant. The positive rate of H3 and H6 subtypes in sewage samples was higher than that in other samples, and the difference was statistically significant. The positive rate of H3, H4 and H6 viruses in the south was higher than that in the north, and the difference was statistically significant. December was the most active time for virus. The analysis of pathogenicity related molecular sites showed that H3, H4 and H6 subtypes of viruses combined with avian influenza virus receptors, and some gene sites related to increased pathogenicity had mutations. Conclusion: The H3, H4 and H6 subtypes of low pathogenic avian influenza viruses have a high isolation positive rate in the live poultry market and sewage. The distribution of the three subtypes of viruses has obvious regional and seasonal characteristics, and the genetic characteristics still show the feature of low pathogenic avian influenza.

Value of Presurgical 18F-FDG PET/CT Radiomics for Predicting Mediastinal Lymph Node Metastasis in Patients with Lung Adenocarcinoma

Objective: The aim of this study was to develop an F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) radiomic model for predicting mediastinal lymph node metastasis (LNM) in presurgical patients with lung adenocarcinoma. Methods: The study enrolled 320 patients with lung adenocarcinoma (288 internal and 32 external cases) and extracted 190 radiomic features using the LIFEx package. Optimal radiomic features to build a radiomic model were selected using the least absolute shrinkage and selection operator algorithm. Logistic regression was used to build the clinical and complex (combined radiomic and clinical variables) models. Results: Ten radiomic features were selected. In the training group, the area under the receiver operating characteristic curve of the complex model was significantly higher than that of the radiomic and clinical models [0.924 (95% CI: 0.887-0.961) vs. 0.863 (95% CI: 0.814-0.912; p = 0.001) and 0.838 (95% CI: 0.783-0.894; p = 0.000), respectively]. The sensitivity, specificity, accuracy, and positive and negative predictive values of the radiomic model were 0.857, 0.790, 0.811, and 0.651 and 0.924, respectively, which were better than that of visual evaluation (0.539, 0.724, 0.667, and 0.472 and 0.775, respectively) and PET semiquantitative analyses (0.619, 0.732, 0.697, and 0.513 and 0.808, respectively). Conclusions: 18F-FDG PET/CT radiomics showed good predictive performance for LNM and improved the N-stage accuracy of lung adenocarcinoma.