Prevalence and treatment rate of gout by depressive symptom severity: A cross-sectional analysis of NHANES 2007-2018.

BACKGROUND: The co-disease of depression and gout is becoming more common in the modern era. However, the relationship between the severity of depressive symptoms and gout prevalence and treatment rate was still unclear. OBJECTIVE: This study aimed to determine the relationship between the prevalence, treatment rate of gout, and the severity of depression in the United States. METHOD: The cross-sectional analysis of the 2007-2018 National Health and Nutrition Examination Survey (NHANES) for participants with depression was performed. According to their Patient Health Questionnaire-9 (PHQ-9) scores, participants were categorized as none, mild, moderate, moderately severe, and severe. To learn the correlation between the severity of depressive symptoms and the prevalence and treatment rate of gout using multivariate logistic regression to control for confounder interference. RESULTS: A total of 25 022 patients were included in this study. As the severity of the depressive symptoms worsened (Mild, Moderate and Moderately severe), the risk of gout increased in non-adjusted model and model 1,2,3 (p-value for trend =.01 in non-adjusted model, <.0001 in model 1, <.01 in models 2 and 3; prevalence group in Model 1, aOR1.71, 95% CI (1.40, 2.08) in the mild group, aOR1.68, 95% CI (1.19, 2.39) in the moderate group, aOR1.31,95% CI (0.82, 2.11) in the moderately severe group, aOR1.21, 95% CI (0.62, 2.38) in the severe group). However, the lower gout prevalence trend has no statistical significance after adjusting all factors in Model 4(p-value for trend =.98). Compared with patients without depression, only a few patients received treatment, especially patients with severe depression (none, 80.1%; severe, 0.2%). The more severe the depression, the lower the treatment rate (p-value for trend: non-adjusted model, p < .001; model 1, p = .05; model 2, p = .02; model 3, p = .03). CONCLUSION: Compared with patients without depression, the patients with depression had a higher risk of gout. With the aggravation of depression, the prevalence of gout and the rate of treatment both were decreased. Patients with gout and depression need to receive multidisciplinary care after diagnosis. However, currently, treatment cannot meet the needs of the current patients.

Injectable and Cell-Laden Hydrogel in the Contained Bone Defect Animal Model: A Systematic Review.

BACKGROUND: Due to its high water content and biomimetic properties simulating extracellular matrix (ECM), hydrogels have been used as preferred cell culture and delivery systems. Similarly, cell-loaded hydrogels can be easily injected into target areas in a minimally invasive manner, minimizing surgical trauma, adapting to irregular shaped defects, and benefiting patients. In this study, we systematically reviewed multiple studies on hydrogel-based bone defect research and briefly summarized the progress of injectable and cell-loaded hydrogels in bone defect repair. METHODS: A systematic search was conducted in the PubMed and Web of Science databases using selected search terms. RESULTS: Initially, 185 articles were retrieved from the databases. After full-text screening based on inclusion and exclusion criteria, 26 articles were included in this systematic review. Data collected from each study included culture model, seed cell type and origin, cell concentration, scaffold material, scaffold shape, experimental animal and site, bioactive agents, and binding method. This injectable and cell-loaded hydrogel shows certain feasibility in bone tissue engineering applications. CONCLUSION: Injectable and cell-loaded hydrogels have been widely applied in bone tissue engineering research. The future direction of bone tissue engineering for bone defect treatment involves the use of new hydrogel materials and biochemical stimulation.

The effect of pore size on the mechanical properties, biodegradation and osteogenic effects of additively manufactured magnesium scaffolds after high temperature oxidation: An in vitro and in vivo study.

The effects of pore size in additively manufactured biodegradable porous magnesium on the mechanical properties and biodegradation of the scaffolds as well as new bone formation have rarely been reported. In this work, we found that high temperature oxidation improves the corrosion resistance of magnesium scaffold. And the effects of pore size on the mechanical characteristics and biodegradation of scaffolds, as well as new bone formation, were investigated using magnesium scaffolds with three different pore sizes, namely, 500, 800, and 1400 µm (P500, P800, and P1400). We discovered that the mechanical characteristics of the P500 group were much better than those of the other two groups. In vitro and in vivo investigations showed that WE43 magnesium alloy scaffolds supported the survival of mesenchymal stem cells and did not cause any local toxicity. Due to their larger specific surface area, the scaffolds in the P500 group released more magnesium ions within reasonable range and improved the osteogenic differentiation of bone mesenchymal stem cells compared with the other two scaffolds. In a rabbit femoral condyle defect model, the P500 group demonstrated unique performance in promoting new bone formation, indicating its great potential for use in bone defect regeneration therapy.

Detecting common coccinellids found in sorghum using deep learning models.

Increased global production of sorghum has the potential to meet many of the demands of a growing human population. Developing automation technologies for field scouting is crucial for long-term and low-cost production. Since 2013, sugarcane aphid (SCA) Melanaphis sacchari (Zehntner) has become an important economic pest causing significant yield loss across the sorghum production region in the United States. Adequate management of SCA depends on costly field scouting to determine pest presence and economic threshold levels to spray insecticides. However, with the impact of insecticides on natural enemies, there is an urgent need to develop automated-detection technologies for their conservation. Natural enemies play a crucial role in the management of SCA populations. These insects, primary coccinellids, prey on SCA and help to reduce unnecessary insecticide applications. Although these insects help regulate SCA populations, the detection and classification of these insects is time-consuming and inefficient in lower value crops like sorghum during field scouting. Advanced deep learning software provides a means to perform laborious automatic agricultural tasks, including detection and classification of insects. However, deep learning models for coccinellids in sorghum have not been developed. Therefore, our objective was to develop and train machine learning models to detect coccinellids commonly found in sorghum and classify them according to their genera, species, and subfamily level. We trained a two-stage object detection model, specifically, Faster Region-based Convolutional Neural Network (Faster R-CNN) with the Feature Pyramid Network (FPN) and also one-stage detection models in the YOLO (You Only Look Once) family (YOLOv5 and YOLOv7) to detect and classify seven coccinellids commonly found in sorghum (i.e., Coccinella septempunctata, Coleomegilla maculata, Cycloneda sanguinea, Harmonia axyridis, Hippodamia convergens, Olla v-nigrum, Scymninae). We used images extracted from the iNaturalist project to perform training and evaluation of the Faster R-CNN-FPN and YOLOv5 and YOLOv7 models. iNaturalist is an imagery web server used to publish citizen's observations of images pertaining to living organisms. Experimental evaluation using standard object detection metrics, such as average precision (AP), AP@0.50, etc., has shown that the YOLOv7 model performs the best on the coccinellid images with an AP@0.50 as high as 97.3, and AP as high as 74.6. Our research contributes automated deep learning software to the area of integrated pest management, making it easier to detect natural enemies in sorghum.

The biological properties of 3D-printed degradable magnesium alloy WE43 porous scaffolds via the oxidative heat strategy.

As a biodegradable material, magnesium alloy has a modulus similar to that of bone, and given the biological activity of its degradation products, it has the potential to be a bone grafting material. Oxidation heat treatment is a very effective passivation method that may reduce the rate of magnesium alloy degradation. Oxidation heat treatment increases the rare earth oxide content of the scaffold as well as the corrosion resistance of the scaffold. The overall cytotoxicity of the as-printed scaffolds (APSs) and oxidation heat-treated scaffolds (OHSs) showed that OHSs accelerated cell proliferation. In the apoptosis experiment, the OHS group had a cell survival rate between that of the control group and of the as-printed group. In the osteogenic induction experiment, the alkaline phosphatase activity and the quantity of mineralized nodules were greater in the APS and OHS groups than in the control group. Marker proteins for bone growth were expressed at higher levels in the APS and OHS groups than in the control group. Therefore, oxidation heat-treated 3D printing scaffolds with good biocompatibility and osteogenic properties have great potential to be made into advanced biomaterials that can be used to fix bone defects.

Development and validation of a novel thoracic spinal stenosis surgical invasiveness index: a single-center study based on 989 patients.

BACKGROUND CONTEXT: Surgical invasiveness indices have been established for general spine surgery (surgical invasiveness index [SII]), spine deformity, and metastatic spine tumors; however, a specific index for thoracic spinal stenosis (TSS) has not been developed. PURPOSE: To develop and validate a novel invasiveness index, incorporating TSS-specific factors for open posterior TSS surgery, which may facilitate the prediction of operative duration and intraoperative blood loss, and the stratification of surgical risk. STUDY DESIGN: A retrospective observational study. PATIENT SAMPLE: Overall, 989 patients who underwent open posterior TSS surgeries at our institution during the past 5 years were included. OUTCOME MEASURES: The operation duration, estimated blood loss, transfusion status, major surgical complications, length of hospital stay, and medical expenses. METHODS: We retrospectively analyzed the data of 989 consecutive patients who underwent posterior surgery for TSS between March 2017 and February 2022. Among them, 70% (n=692) were randomly placed in a training cohort, and the remaining 30% (n=297) automatically constituted the validation cohort. Multivariate linear regression models of operative time and log-transformed estimated blood loss were created using TSS-specific factors. Beta coefficients derived from these models were used to construct a TSS invasiveness index (TII). The ability of the TII to predict surgical invasiveness was compared with that of the SII and assessed in a validation cohort. RESULTS: The TII was more strongly correlated with operative time and estimated blood loss (p<.05) and explained more variability in operative time and estimated blood loss than the SII (p<.05). The TII explained 64.2% of operative time and 34.6% of estimated blood loss variation, whereas the SII explained 38.7% and 22.5%, respectively. In further verification, the TII was more strongly associated with transfusion rate, drainage time, and length of hospital stay than SII (p<.05). CONCLUSIONS: By incorporating TSS-specific components, the newly developed TII more accurately predicts the invasiveness of open posterior TSS surgery than the previous index.

Meta-QTL and haplo-pheno analysis reveal superior haplotype combinations associated with low grain chalkiness under high temperature in rice.

Chalk, an undesirable grain quality trait in rice, is primarily formed due to high temperatures during the grain-filling process. Owing to the disordered starch granule structure, air spaces and low amylose content, chalky grains are easily breakable during milling thereby lowering head rice recovery and its market price. Availability of multiple QTLs associated with grain chalkiness and associated attributes, provided us an opportunity to perform a meta-analysis and identify candidate genes and their alleles contributing to enhanced grain quality. From the 403 previously reported QTLs, 64 Meta-QTLs encompassing 5262 non-redundant genes were identified. MQTL analysis reduced the genetic and physical intervals and nearly 73% meta-QTLs were narrower than 5cM and 2Mb, revealing the hotspot genomic regions. By investigating expression profiles of 5262 genes in previously published datasets, 49 candidate genes were shortlisted on the basis of their differential regulation in at least two of the datasets. We identified non-synonymous allelic variations and haplotypes in 39 candidate genes across the 3K rice genome panel. Further, we phenotyped a subset panel of 60 rice accessions by exposing them to high temperature stress under natural field conditions over two Rabi cropping seasons. Haplo-pheno analysis uncovered haplotype combinations of two starch synthesis genes, GBSSI and SSIIa, significantly contributing towards the formation of grain chalk in rice. We, therefore, report not only markers and pre-breeding material, but also propose superior haplotype combinations which can be introduced using either marker-assisted breeding or CRISPR-Cas based prime editing to generate elite rice varieties with low grain chalkiness and high HRY traits.

Algal polysaccharides-Selenium nanoparticles regulate the uptake and distribution of selenium in rice plants.

Introduction: Selenium (Se) is an essential trace element required for proper human and animal health. Methods: In this paper, we investigated the uptake and distribution characteristics of a new Se fertilizer, which comprises algal polysaccharides-selenium nanoparticles (APS-SeNPs), in rice plants in both hydroponic and pot experiments. Results: The results from the hydroponic experiments revealed that the rice root uptake of APS-SeNPs fitted the Michaelis-Menten equation, with a V max of 13.54 µg g-1 root dry weight (DW) per hour, which was 7.69 and 2.23 times those of selenite and selenate treatments, respectively. The root uptake of APS-SeNPs was inhibited by AgNO3 (64.81%-79.09%) and carbonyl cyanide 3-chlorophenylhydrazone (CCCP; 19.83%-29.03%), indicating that the uptake of APS-SeNPs by rice roots is mainly via aquaporins and is also affected by metabolic activity. Moreover, sulfur deficiency caused rice roots to absorb more APS-SeNPs, but treatment with APS-SeNPs increased the expression of the sulfate transporter OsSULTR1;2 in the roots, suggesting that OsSULTR1;2 is probably involved in the uptake of APS-SeNPs. The application of APS-SeNPs significantly increased the Se content in rice plants and the apparent Se uptake efficiency compared with selenate and selenite treatments. Most of the Se in the roots of rice plants was distributed in the cell wall, while it was primarily located in the cytosol in the shoots when treated with APS-SeNPs. The results from the pot experiments indicated that the application of Se enhanced the Se content of each rice tissue. It is worth noting that the Se content in brown rice under APS-SeNP treatment was higher than that under selenite or selenate treatment and was mainly concentrated in the embryo end, with the Se in organic form. Discussion: Our findings provide important insights into the uptake mechanism and the distribution of APS-SeNPs in rice plants.

SAPHO syndrome with Takayasu arteritis successfully treated with tofacitinib.

SAPHO syndrome is an autoinflammatory disease with a variety of clinical manifestations, which may be accompanied by other systemic inflammatory diseases in addition to the typical manifestations of common synovitis, acne, pustulosis, hyperostosis, and osteitis. Here, we report the first case of SAPHO syndrome combined with Takayasu arteritis.

Deep learning based high-throughput phenotyping of chalkiness in rice exposed to high night temperature.

BACKGROUND: Rice is a major staple food crop for more than half the world's population. As the global population is expected to reach 9.7 billion by 2050, increasing the production of high-quality rice is needed to meet the anticipated increased demand. However, global environmental changes, especially increasing temperatures, can affect grain yield and quality. Heat stress is one of the major causes of an increased proportion of chalkiness in rice, which compromises quality and reduces the market value. Researchers have identified 140 quantitative trait loci linked to chalkiness mapped across 12 chromosomes of the rice genome. However, the available genetic information acquired by employing advances in genetics has not been adequately exploited due to a lack of a reliable, rapid and high-throughput phenotyping tool to capture chalkiness. To derive extensive benefit from the genetic progress achieved, tools that facilitate high-throughput phenotyping of rice chalkiness are needed. RESULTS: We use a fully automated approach based on convolutional neural networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM) to detect chalkiness in rice grain images. Specifically, we train a CNN model to distinguish between chalky and non-chalky grains and subsequently use Grad-CAM to identify the area of a grain that is indicative of the chalky class. The area identified by the Grad-CAM approach takes the form of a smooth heatmap that can be used to quantify the degree of chalkiness. Experimental results on both polished and unpolished rice grains using standard instance classification and segmentation metrics have shown that Grad-CAM can accurately identify chalky grains and detect the chalkiness area. CONCLUSIONS: We have successfully demonstrated the application of a Grad-CAM based tool to accurately capture high night temperature induced chalkiness in rice. The models trained will be made publicly available. They are easy-to-use, scalable and can be readily incorporated into ongoing rice breeding programs, without rice researchers requiring computer science or machine learning expertise.

Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents.

Drug discovery relies on the knowledge of not only drugs and targets, but also the comparative agents and targets. These include poor binders and non-binders for developing discovery tools, prodrugs for improved therapeutics, co-targets of therapeutic targets for multi-target strategies and off-target investigations, and the collective structure-activity and drug-likeness landscapes of enhanced drug feature. However, such valuable data are inadequately covered by the available databases. In this study, a major update of the Therapeutic Target Database, previously featured in NAR, was therefore introduced. This update includes (a) 34 861 poor binders and 12 683 non-binders of 1308 targets; (b) 534 prodrug-drug pairs for 121 targets; (c) 1127 co-targets of 672 targets regulated by 642 approved and 624 clinical trial drugs; (d) the collective structure-activity landscapes of 427 262 active agents of 1565 targets; (e) the profiles of drug-like properties of 33 598 agents of 1102 targets. Moreover, a variety of additional data and function are provided, which include the cross-links to the target structure in PDB and AlphaFold, 159 and 1658 newly emerged targets and drugs, and the advanced search function for multi-entry target sequences or drug structures. The database is accessible without login requirement at: https://idrblab.org/ttd/.

Protein music of enhanced musicality by music style guided exploration of diverse amino acid properties.

Inspired by the traceable analogies between protein sequences and music notes, protein music has been composed from amino acid sequences for popularizing science and sourcing melodies. Despite the continuous development of protein-to-music algorithms, the musicality of protein music lags far behind human music. Musicality may be enhanced by fine-tuned protein-to-music mapping to the features of a specific music style. We analyzed the features of a music style (Fantasy-Impromptu style), and used the quantized musical features to guide broad exploration of diverse amino acid properties (104 properties, sequence patterns and variations) for developing a novel protein-to-music algorithm of enhanced musicality. This algorithm was applied to 18 proteins of various biological functions. The derived music pieces consistently exhibited enhanced musicality with respect to existing protein music. Music style guided exploration of diverse amino acid properties enable protein music composition of enhanced musicality, which may be further developed and applied to a wider variety of music styles.

Salmonella Osteomyelitis in Adults: A Systematic Review.

The aim of this systematic review was to characterize the clinical features of adults with Salmonella osteomyelitis and summarize diagnosis and treatment methods to provide guidance for clinicians. This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We conducted a literature search in the PubMed, EMBASE, and Cochrane Library databases. Article screening and data extraction were performed by two reviewers individually. All the included studies were independently evaluated by two reviewers using the Methodological Index for Non-Randomized Studies (MINORS) criteria. A total of 67 articles published between 1970 and 2019 were selected, which include 69 patients with an average age of 47.5 years (range, 18-79).The majority of cases (47.76%) occurred in immunocompetent adults without common risk factors. Aspiration and biopsy cultures were all positive in Salmonella osteomyelitis patients who underwent aspiration or biopsy. All infections were monomicrobial, and a total of 12 different serotypes were identified. The three most commonly reported Salmonella serotypes were Salmonella typhi (19 cases), Salmonella typhimurium (12 cases), and Salmonella enteritidis (11 cases). Only 12 of the 67 cases in our data (17.91%) had diarrhea symptoms, and 44 of the 67 cases (65.67%) had fever symptoms. Fifty-nine of the 67 cases (88.06%) had local inflammatory manifestations, such as erythema, swelling, and tenderness in the affected area. The commonly reported involved sites were the vertebrae, femur, and tibia. Antibiotic therapy alone was utilized in 30 cases, and 24 patients (80.00%) were eventually cured. In total, 75.68% of patients achieved satisfactory results after treatment with surgery and antibiotics. Third-generation cephalosporins were most commonly utilized, and antibiotic treatment was administered for an average of 11.3 weeks (95% CI, 8.31-14.37 weeks). Salmonella osteomyelitis should be considered in patients without any common risk factors. Aspiration or biopsy can facilitate the identification of pathogens to guide antibiotic choice. Empirical therapy with a third-generation cephalosporin is recommended until the susceptibility of the strain is determined.

Classical phenotyping and deep learning concur on genetic control of stomatal density and area in sorghum.

Stomatal density (SD) and stomatal complex area (SCA) are important traits that regulate gas exchange and abiotic stress response in plants. Despite sorghum (Sorghum bicolor) adaptation to arid conditions, the genetic potential of stomata-related traits remains unexplored due to challenges in available phenotyping methods. Hence, identifying loci that control stomatal traits is fundamental to designing strategies to breed sorghum with optimized stomatal regulation. We implemented both classical and deep learning methods to characterize genetic diversity in 311 grain sorghum accessions for stomatal traits at two different field environments. Nearly 12,000 images collected from abaxial (Ab) and adaxial (Ad) leaf surfaces revealed substantial variation in stomatal traits. Our study demonstrated significant accuracy between manual and deep learning methods in predicting SD and SCA. In sorghum, SD was 32%-39% greater on the Ab versus the Ad surface, while SCA on the Ab surface was 2%-5% smaller than on the Ad surface. Genome-Wide Association Study identified 71 genetic loci (38 were environment-specific) with significant genotype to phenotype associations for stomatal traits. Putative causal genes underlying the phenotypic variation were identified. Accessions with similar SCA but carrying contrasting haplotypes for SD were tested for stomatal conductance and carbon assimilation under field conditions. Our findings provide a foundation for further studies on the genetic and molecular mechanisms controlling stomata patterning and regulation in sorghum. An integrated physiological, deep learning, and genomic approach allowed us to unravel the genetic control of natural variation in stomata traits in sorghum, which can be applied to other plants.

Immunometabolism and potential targets in severe COVID-19 peripheral immune responses.

Graphical Abstract Image, graphical abstract.

Rare Occurrence of Acute Hematogenous Periprosthetic Joint Infection Due to Fusobacterium Nucleatum in the Background of a Dental Procedure: A Case Report.

OBJECTIVE: Fusobacterium nucleatum is an anaerobic gram-negative bacilli that is one of the oral and other mucosal surface microbiota. It involves a wide range of human diseases and was first found in periodontal diseases, but reports of bone-related infections caused by F. nucleatum are rare, especially periprosthetic joint infections (PJI). METHODS: Here, we present the first case of acute hematogenous PJI of the hip joint caused by F. nucleatum, and debridement, antibiotics, and implant retention (DAIR) was performed. RESULTS: The patient was successfully treated with DAIR, identification of isolates by metagenomics next-generation sequencing was confirmed by polymerase chain reaction. CONCLUSIONS: For stable acute hematogenous PJI after hip replacement, quick and accurate diagnosis, the identification of pathogenic microorganisms, and the use of DAIR combined with sufficient sensitive antibiotics have a certain clinical effect and can achieve the purpose of both preserving the prosthesis and infection control.

Cup-Cage Solution for Massive Acetabular Defects: A Systematic Review and Meta-Analysis.

Our systematic review compiled multiple studies and evaluated survivorship and clinical outcomes of cup-cage construct usage in the management of massive acetabular bone defects. This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Various combinations of "acetabular", "pelvis", "cup cage" and their corresponding synonyms were used to search relevant articles in the Cochrane, EMBASE, and PubMed databases. Basic information of the functional scores, implant revision rate, and complication rate were selected as outcomes for analysis. Finally, a total of 11 articles published between 1999 and 2019 were selected, which include 232 patients with an average age of 68.5 years (range, 30-90). The mean follow-up period was 48.85 months (range, 1-140). Our study shows that the cup-cage construct has a good clinical outcome with a low revision rate and a low complication rate. Improved clinical outcomes of cup-cage constructs were seen with a revision rate of 8% and an all-cause complication rate of 20%. The most commonly reported complication was dislocation, followed by aseptic loosening, infection, and nerve injuries. In summary, it is a promising method for managing large acetabular bone defects in total hip revision.

Preliminary assessment of nanopore-based metagenomic sequencing for the diagnosis of prosthetic joint infection.

OBJECTIVES: Pathogen identification is crucial for the diagnosis and management of periprosthetic joint infection (PJI). Although culturing methods are the foundation of pathogen detection in PJI, false-negative results often occur. Oxford nanopore sequencing (ONS) is a promising alternative for detecting pathogens and providing information on their antimicrobial resistance (AMR) profiles, without culturing. METHODS: To evaluate the capability of metagenomic ONS (mONS) in detecting pathogens from PJI samples, both metagenomic next-generation sequencing (mNGS) and mONS were performed in 15 osteoarticular samples from nine consecutive PJI patients according to the modified Musculoskeletal Infection Society (MSIS) criteria. The sequencing data generated from both platforms were then analyzed for pathogen identification and AMR detection using an in-house-developed bioinformatics pipeline. RESULTS: Our results showed that mONS could be applied to detect the causative pathogen and characterize its AMR features in fresh PJI samples. By real-time sequencing and analysis, pathogen identification and AMR detection from the initiation of sequencing were accelerated. CONCLUSION: We showed proof of concept that mONS can function as a rapid, accurate tool in PJI diagnostic microbiology. Despite efforts to reduce host DNA, the high proportion of host DNA was still a limitation of this method that prevented full genome analysis.

Comparison of broad-range polymerase chain reaction and metagenomic next-generation sequencing for the diagnosis of prosthetic joint infection.

PURPOSE: The aims of our study were to (1) evaluate the concordance of both methods for detecting prosthetic joint infection (PJI) pathogens in joint fluid and to (2) clarify whether broad-range polymerase chain reaction (BR-PCR) can be used as a verification method for metagenomic next-generation sequencing (mNGS) for PJI diagnosis. METHODS: In total, 63 patients underwent total joint arthroplasty, with 45 PJI and 18 aseptic failure patients included. Joint fluids were sampled after antibiotics were withheld for more than 2 weeks, and then, culture, BR-PCR and mNGS were performed for all samples. RESULTS: The joint fluid BR-PCR sensitivity was 82.2%, which was not significantly different from that of mNGS (95.6%) or culture (77.8%). The specificities of the 3 methods were all 94.4%. BR-PCR failed to identify the pathogens in 1 polymicrobial infection patient and 4 fungal infection patients. CONCLUSION: mNGS was more sensitive than BR-PCR for detecting PJI pathogens in joint fluid. BR-PCR is insufficient for use as an mNGS verification method.

Can metagenomic next-generation sequencing identify the pathogens responsible for culture-negative prosthetic joint infection?

BACKGROUND: The aims of this study were to (1) evaluate the efficacy and safety of targeted antibiotics for the treatment of culture-negative prosthetic joint infection based on metagenomic next-generation sequencing results and (2) verify the accuracy and reliability of metagenomic next-generation sequencing for identifying pathogens related to culture-negative prosthetic joint infection. METHODS: Ninety-seven consecutive PJI patients, including 27 patients with culture-negative prosthetic joint infection, were treated surgically at our center. Thirteen of the 27 culture-negative prosthetic joint infection patients, who were admitted before June 2017 and treated with empirical antibiotics, comprised the empirical antibiotic group (EA group), and the other 14 patients, who were admitted after June 2017 and treated with targeted antibiotics according to their metagenomic next-generation sequencing results, were classified as the targeted antibiotic group (TA group). The short-term infection control rate, incidence of antibiotic-related complications and costs were compared between the two groups. RESULTS: Two of the patients in the EA group experienced debridement and prolonged antimicrobial therapy due to wound infection after the initial revision surgery. No recurrent infections were observed in the TA group; however, no significant difference in the infection control rate was found between the two groups (83.33% vs 100%, P = 0.217). More cases of antibiotic-related complications were recorded in the EA group (6 cases) than in the TA group (1 case), but the difference was not statistically significant (P = 0.0697). The cost of antibiotics obtained for the EA group was 20,168.37 Yuan (3236.38-45,297.16), which was higher than that found for the TA group (10,164.16 Yuan, 2959.54-16,661.04, P = 0.04). CONCLUSIONS: Targeted antibiotic treatment for culture-negative prosthetic joint infection based on metagenomic next-generation sequencing results is associated with a favorable outcome, and metagenomic next-generation sequencing is a reliable tool for identifying pathogens related to culture-negative prosthetic joint infection.