Diffusion-weighted imaging-based radiomics model using automatic machine learning to differentiate cerebral cystic metastases from brain abscesses.

OBJECTIVES: To develop a radiomics model based on diffusion-weighted imaging (DWI) utilizing automated machine learning method to differentiate cerebral cystic metastases from brain abscesses. MATERIALS AND METHODS: A total of 186 patients with cerebral cystic metastases (n = 98) and brain abscesses (n = 88) from two clinical institutions were retrospectively included. The datasets (129 from institution A) were randomly portioned into separate 75% training and 25% internal testing sets. Radiomics features were extracted from DWI images using two subregions of the lesion (cystic core and solid wall). A thorough image preprocessing method was applied to DWI images to ensure the robustness of radiomics features before feature extraction. Then the Tree-based Pipeline Optimization Tool (TPOT) was utilized to search for the best optimized machine learning pipeline, using a fivefold cross-validation in the training set. The external test set (57 from institution B) was used to evaluate the model's performance. RESULTS: Seven distinct TPOT models were optimized to distinguish between cerebral cystic metastases and abscesses either based on different features combination or using wavelet transform. The optimal model demonstrated an AUC of 1.00, an accuracy of 0.97, sensitivity of 1.00, and specificity of 0.93 in the internal test set, based on the combination of cystic core and solid wall radiomics signature using wavelet transform. In the external test set, this model reached 1.00 AUC, 0.96 accuracy, 1.00 sensitivity, and 0.93 specificity. CONCLUSION: The DWI-based radiomics model established by TPOT exhibits a promising predictive capacity in distinguishing cerebral cystic metastases from abscesses.

Perivascular fat attenuation index value and plaque volume increased in non-target lesions of coronary arteries after stenting.

BACKGROUND: Progression of non-target lesions (NTLs) after stenting has been reported and is associated with the triggering of an inflammatory response. The perivascular fat attenuation index (FAI) may be used as a novel imaging biomarker for the direct quantification of coronary inflammation. OBJECTIVES: To investigate whether FAI values can help identify changes in inflammation status in patients undergoing stent implantation, especially in NTLs. METHODS: Patients who underwent pre- and post-stenting coronary computed tomography angiography (CCTA) examination between January 2015 and February 2021 were consecutively enrolled. The pre- and post-stenting FAIs of the full coronary arteries were compared in both the non- and stent-implanted coronary arteries. Moreover, local FAI values were measured and compared between the NTLs and target lesions in the stent implantations. We also compared changes in plaque type and volume in NTLs before and after stenting. RESULTS: A total of 89 patients (mean age 61 years; male 59) were enrolled. The perivascular FAI values in the full coronary arteries decreased after stenting in both the non- and stent-implanted coronary arteries, similar to those in the target lesions. Conversely, the perivascular FAI values in the NTLs increased after stenting (p < 0.05). In addition, the plaque volumes significantly increased in the NTLs after stenting, regardless of whether they were non-calcified, mixed, or calcified (p < 0.05). CONCLUSION: Perivascular FAI values and plaque volumes increased in the NTLs after stenting. Perivascular FAI can be a promising imaging biomarker for monitoring coronary inflammation after stenting and facilitate long-term monitoring in clinical settings. CLINICAL RELEVANCE STATEMENT: Perivascular fat attenuation index, a non-invasive imaging biomarker, may help identify coronary arteries with high inflammation in non-target lesions and facilitate long-term monitoring, potentially providing an opportunity for more targeted treatment. KEY POINTS: • Perivascular fat attenuation index (FAI) values and plaque volumes increased in the non-target lesions (NTLs) after stenting, suggesting potential focal inflammation progression after stenting. However, stenting along with anti-inflammatory treatment ameliorated inflammation in the full coronary arteries. • Perivascular FAI, a non-invasive imaging biomarker, may help identify coronary arteries with high inflammation in NTLs and facilitate long-term monitoring, potentially providing an opportunity for more targeted treatment.

Sex-Specific Computed Tomography Abdominal Fat and Skeletal Muscle Characteristics in Type 2 Diabetic Retinopathy Patients With/Without Comorbid Diabetic Kidney Disease.

RATIONALE AND OBJECTIVES: To investigate differences in sex-specific computed tomography abdominal fat and skeletal muscle (SM) characteristics between type 2 diabetic retinopathy (DR) patients with and without diabetic kidney disease (DKD). MATERIALS AND METHODS: This retrospective study included type 2 diabetes mellitus DR patients with/without DKD between January 2019 and July 2021. Visceral adipose tissue (VAT), subcutaneous adipose tissue, perirenal adipose tissue (PAT), intramuscular adipose tissue, and SM areas were measured. Univariate and multivariate logistic regression analyses were used to analyze risk factors for DKD. Correlation and multiple linear regression analyses were used to clarify the association between computed tomography abdominal fat, SM characteristics, and cystatin C. RESULTS: Two hundred and forty-one patients were enrolled and divided into DR with DKD group (n = 142) and DR without DKD group (n = 99). In men, hypertension (OR: 5.21; 95%CI: 1.93-14.05; p = 0.001), diastolic pressure (OR: 1.07; 95%CI: 1.01-1.12; p = 0.011), hemoglobin (OR: 0.94; 95%CI: 0.92-0.97; p < 0.001) and PAT attenuation value (OR: 1.09; 95%CI: 1.01-1.17; p = 0.026) were independent risk factors for DKD progression in DR patients, while the VAT index (VATI) (OR: 1.03; 95%CI: 1.01-1.05; p = 0.014) was an independent risk factor for female patients. Multiple linear regression analysis revealed significant correlations between hypertension (ß = 0.22, p = 0.002) and hemoglobin (ß = -0.53, p < 0.001) with cystatin C in men, and a significant correlation between VATI and cystatin C (ß = 0.35, p = 0.037) in women after adjustment for confounders. CONCLUSION: Female DR patients with elevated VAT level may suffer from a higher risk of DKD than that in male patients.

Analysis of Antimicrobial Resistance and Genetic Correlations of Escherichia Coli in Dairy Cow Mastitis.

Introduction: Escherichia coli is a widespread environmental pathogen frequently causing dairy cow mastitis. This bacterium is particularly capable of acquiring antimicrobial resistance, which can have severe impacts on animal food safety and human health. The objective of the study was to investigate antimicrobial resistance and genetic correlations of E. coli from dairy cow mastitis cases in northern China. Material and Methods: Forty strains of E. coli from 196 mastitis milk samples were collected, susceptibility to 13 common antibiotics and the prevalence of resistance genes were tested in these strains, and the genetic characteristics were identified by multilocus sequence typing. Results: The results showed that most isolates were multidrug resistant (MDR) (75%), and the resistance rates to cefazolin, trimethoprim-sulfamethoxazole and ampicillin were 77.5%, 55.0%, and 52.5%, respectively. The representative genes of the isolates were aadA (62.5%) and tet(B) (60.0%). Multilocus sequence typing showed 19 different sequence types (STs) and 5 clonal complexes (CCs) in the 40 isolates, mainly represented by ST10 and CC10. The strains of the same ST or CC showed a high level of genetic relatedness, but the characteristics of their antimicrobial resistance were markedly different. Conclusion: Most E. coli isolates in the study were MDR strains. Some strains of the same ST or CC showed diverse resistance characteristics to common antimicrobials. Therefore, E. coli from dairy cow mastitis in northern China should be investigated to elucidate its antimicrobial resistance and genotypes.

BHBA regulates the expressions of lipid synthesis and oxidation genes in sheep hepatocytes through the AMPK pathway.

Pregnancy toxemia (PT) is the most frequent metabolic disease of sheep during late pregnancy, which can lead to enormous economic losses in sheep farm industry. However, the underlying mechanism of PT in sheep has not been fully elucidated. High levels of ß-hydroxy butyric acid (BHBA) exist in PT sheep. The AMP-activated protein kinase (AMPK) pathway plays a major role in regulating liver function. The aim of this study was to explore the effects of gradient concentrations of BHBA on lipid metabolism of sheep hepatocytes and the underlying molecular mechanism in vitro. The results showed that 0.6, 1.2 mmol/L BHBA could activate AMPKα, promoted the expressions of peroxisome proliferator-activated receptor alpha (PPARα) and its target genes, and inhibited the expressions of sterol regulatory element binding protein-1c (SREBP-1c) as well as its downstream genes. When the concentration of BHBA was beyond 1.2 mmol/L, the expressions of the above-mentioned proteins and genes were just the opposite. However, the expressions of adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL) did not change significantly. The levels of very low density lipoprotein (VLDL), triglyceride (TG) and cholesterol (T-CHOL) showed a gradually increasing trend with the increase of BHBA concentration. According to the results above, it demonstrates that high levels of BHBA can inhibit the expression of the AMPK pathway and cause lipid metabolism disorders in sheep hepatocytes, which may lead to the occurrence of PT.