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Introduction: Chronic osteomyelitis is a complex clinical condition that is associated with a high recurrence rate. Traditional surgical interventions often face challenges in achieving a balance between thorough debridement and managing resultant bone defects. Radiomics is an emerging technique that extracts quantitative features from medical images to reveal pathological information imperceptible to the naked eye. This study aims to investigate the potential of radiomics in optimizing osteomyelitis diagnosis and surgical treatment.Methods: Magnetic resonance imaging (MRI) scans of 93 suspected osteomyelitis patients were analyzed. Radiomics features were extracted from the original lesion region of interest (ROI) and an expanded ROI delineated by enlarging the original by 5 mm. Feature selection was performed and support vector machine (SVM) models were developed using the two ROI datasets. To assess the diagnostic efficacy of the established models, we conducted receiver operating characteristic (ROC) curve analysis, employing histopathological results as the reference standard. The model’s performance was evaluated by calculating the area under the curve (AUC), sensitivity, specificity, and accuracy. Discrepancies in the ROC between the two models were evaluated using the DeLong method. All statistical analyses were carried out using Python, and a significance threshold of p < 0.05 was employed to determine statistical significance.Results and Discussion: A total of 1,037 radiomics features were extracted from each ROI. The expanded ROI model achieved significantly higher accuracy (0.894 vs. 0.821), sensitivity (0.947 vs. 0.857), specificity (0.842 vs. 0.785) and AUC (0.920 vs. 0.859) than the original ROI model. Key discriminative features included shape metrics and wavelet-filtered texture features. Radiomics analysis of MRI exhibits promising clinical translational potential in enhancing the diagnosis of chronic osteomyelitis by accurately delineating lesions and identifying surgical margins. The inclusion of an expanded ROI that encompasses perilesional tissue significantly improves diagnostic performance compared to solely focusing on the lesions. This study provides clinicians with a more precise and effective tool for diagnosis and surgical decision-making, ultimately leading to improved outcomes in this patient population.

BackgroundPorcine deltacoronavirus (PDCoV), a novel swine enteropathogenic coronavirus, challenges the global swine industry. Currently, there are no approaches preventing swine from PDCoV infection.MethodsA new PDCoV strain named JS2211 was isolated. Next, the dimer receptor binding domain of PDCoV spike protein (RBD-dimer) was expressed using the prokaryotic expression system, and a novel nanoparticle containing RBD-dimer and ferritin (SC-Fe) was constructed using the SpyTag/SpyCatcher system. Finally, the immunoprotection of RBD-Fe nanoparticles was evaluated in mice.ResultsThe novel PDCoV strain was located in the clade of the late Chinese isolate strains and close to the United States strains. The RBD-Fe nanoparticles were successfully established. Immune responses of the homologous prime-boost regime showed that RBD-Fe nanoparticles efficiently elicited specific humoral and cellular immune responses in mice. Notably, high level PDCoV RBD-specific IgG and neutralizing antibody (NA) could be detected, and the histopathological results showed that PDCoV infection was dramatically reduced in mice immunized with RBD-Fe nanoparticles.ConclusionThis study effectively developed a candidate nanoparticle with receptor binding domain of PDCoV spike protein that offers protection against PDCoV infection in mice.

Abstract The “dimensional stability” approach measures different components of ecological stability to investigate how they are related. Yet, most empirical work has used small‐scale and short‐term experimental manipulations. Here, we apply this framework to a long‐term observational dataset of stream macroinvertebrates sampled between the winter flooding and summer monsoon seasons. We test hypotheses that relate variation among stability metrics across different taxa, the magnitude of antecedent (monsoon) and immediate (winter) floods to stability metrics, and the relative importance of disturbance magnitude and taxonomic richness on community dimensional stability. Cluster analysis revealed four distinct stability types, and we found that the magnitude of floods during the prior monsoon was more important in influencing stability than the winter flood itself. For dimensional stability at the community level, taxonomic richness was more important than disturbance magnitude. This work demonstrates that abiotic and biotic factors determine dimensional stability in a natural ecosystem.

ABSTRACT ST11-KL64 is an internationally distributed lineage of carbapenem-resistant Klebsiella pneumoniae and is the most common type in China. The international and interprovincial (in China) transmission of ST11-KL64 CRKP remains to be elucidated. We used both static clusters defined based on a fixed cutoff of ≤21 pairwise single-nucleotide polymorphisms and dynamic groups defined by modeling the likelihood to be linked by a transmission threshold to investigate the transmission of ST11-KL64 strains based on genome sequences mining. We analyzed all publicly available genomes (n = 730) of ST11-KL64 strains, almost all of which had known carbapenemase genes with KPC-2 being dominant. We identified 4 clusters of international transmission and 14 clusters of interprovincial transmission across China of ST11-KL64 strains. We found that dynamic grouping could provide further resolution for determining clonal relatedness in addition to the widely adopted static clustering and therefore increases the confidence for inferring transmission. Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a serious challenge for clinical management and is prone to spread in and between healthcare settings. ST11-KL64 is the dominant CRKP type in China with a worldwide distribution. Here, we used two different methods, the widely used clustering based on a fixed single-nucleotide polymorphism (SNP) cutoff and the recently developed grouping by modeling transmission likelihood, to mine all 730 publicly available ST11-KL64 genomes. We identified international transmission of several strains and interprovincial transmission in China of a few, which warrants further investigations to uncover the mechanisms for their spread. We found that static clustering based on ≤21 fixed SNPs is sensitive to detect transmission and dynamic grouping has higher resolutions to provide complementary information. We suggest the use of the two methods in combination for analyzing transmission of bacterial strains. Our findings highlight the need of coordinated actions at both international and interprovincial levels for tackling multi-drug resistant organisms.

Thermal-denatured whey protein-milk fat emulsion gels with different degrees of pre-emulsification were prepared by pre-emulsifying milk fat with thermal-denatured whey protein and used in the preparation of reduced-sodium processed cheeses. The effect of the thermal-denatured whey protein pre-emulsification process on the texture and microstructure of reduced-sodium processed cheeses was evaluated by studying the composition, color, texture, functional properties, microstructure and sensory analysis of the processed cheeses. The results showed that compared with cheese without pre-emulsified fat (1.5% ES control), the moisture content of cheese with pre-emulsified 100% fat (1.5% ES100) increased by 5.81%, the L* values increased by 7.61%, the hardness increased by 43.24%, and the free oil release decreased by 38%. The microstructure showed that the particle size of fat was significantly reduced, and the distribution was more uniform. In addition, compared with the cheese added with 3% emulsifying salt (3% ES control), the amount of emulsifying salt in the 1.5% ES100 decreased by 50%, but the fat distribution of the two kinds of cheese tended to be consistent, and there was no obvious change in texture characteristics and meltability. Sensory scores increased with the increase in pre-emulsification degree. Overall, the pre-emulsification of milk fat with thermal-denatured whey protein can reduce the sodium content of processed cheese and improve its quality.

This study investigates mechanisms that generate regularly spaced iron-rich bands in upland soils. These striking features appear in soils worldwide, but beyond a generalized association with changing redox, their genesis is yet to be explained. Upland soils exhibit significant redox fluctuations driven by rainfall, groundwater changes, or irrigation. Pattern formation in such systems provides an opportunity to investigate the temporal aspects of spatial self-organization, which have been heretofore understudied. By comparing multiple alternative mechanisms, we found that regular iron banding in upland soils is explained by coupling two sets of scale-dependent feedbacks, the general principle of Turing morphogenesis. First, clay dispersion and coagulation in iron redox fluctuations amplify soil Fe(III) aggregation and crystal growth to a level that negatively affects root growth. Second, the activation of this negative root response to highly crystalline Fe(III) leads to the formation of rhythmic iron bands. In forming iron bands, environmental variability plays a critical role. It creates alternating anoxic and oxic conditions for required pattern-forming processes to occur in distinctly separated times and determines durations of anoxic and oxic episodes, thereby controlling relative rates of processes accompanying oxidation and reduction reactions. As Turing morphogenesis requires ratios of certain process rates to be within a specific range, environmental variability thus modifies the likelihood that pattern formation will occur. Projected changes of climatic regime could significantly alter many spatially self-organized systems, as well as the ecological functioning associated with the striking patterns they present. This temporal dimension of pattern formation merits close attention in the future. [ABSTRACT FROM AUTHOR]

The “dimensional stability” approach measures different components of ecological stability to investigate how they are related. Yet, most empirical work has used small-scale and short-term experimental manipulations. Here, we apply this framework to a long-term observational dataset of stream macroinvertebrates sampled between the winter flooding and summer monsoon seasons. We test hypotheses that relate variation among stability metrics across different taxa, the magnitude of antecedent (monsoon) and immediate (winter) floods to stability metrics, and the relative importance of disturbance magnitude and taxonomic richness on community dimensional stability. Cluster analysis revealed four distinct stability types, and we found that the magnitude of floods during the prior monsoon was more important in influencing stability than the winter flood itself. For dimensional stability at the community level, taxonomic richness was more important than disturbance magnitude. This work demonstrates that abiotic and biotic factors determine dimensional stability in a natural ecosystem. [ABSTRACT FROM AUTHOR]