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Infection, as a common postoperative complication of orthopedic surgery, is the main reason leading to implant failure. Silver nanoparticles (AgNPs) are considered as a promising antibacterial agent and always used to modify orthopedic implants to prevent infection. To optimize the implants in a reasonable manner, it is critical for us to know the specific antibacterial mechanism, which is still unclear. In this review, we analyzed the potential antibacterial mechanisms of AgNPs, and the influences of AgNPs on osteogenic-related cells, including cellular adhesion, proliferation, and differentiation, were also discussed. In addition, methods to enhance biocompatibility of AgNPs as well as advanced implants modifications technologies were also summarized.

Background Accurately diagnosing supraspinatus tears based on magnetic resonance imaging (MRI) is challenging and time-combusting due to the experience level variability of the musculoskeletal radiologists and orthopedic surgeons. We developed a deep learning-based model for automatically diagnosing supraspinatus tears (STs) using shoulder MRI and validated its feasibility in clinical practice. Materials and methods A total of 701 shoulder MRI data (2804 images) were retrospectively collected for model training and internal test. An additional 69 shoulder MRIs (276 images) were collected from patients who underwent shoulder arthroplasty and constituted the surgery test set for clinical validation. Two advanced convolutional neural networks (CNN) based on Xception were trained and optimized to detect STs. The diagnostic performance of the CNN was evaluated according to its sensitivity, specificity, precision, accuracy, and F1 score. Subgroup analyses were performed to verify its robustness, and we also compared the CNN’s performance with that of 4 radiologists and 4 orthopedic surgeons on the surgery and internal test sets. Results Optimal diagnostic performance was achieved on the 2D model, from which F1-scores of 0.824 and 0.75, and areas under the ROC curves of 0.921 (95% confidence interval, 0.841–1.000) and 0.882 (0.817–0.947) were observed on the surgery and internal test sets. For the subgroup analysis, the 2D CNN model demonstrated a sensitivity of 0.33–1.000 and 0.625–1.000 for different degrees of tears on the surgery and internal test sets, and there was no significant performance difference between 1.5 and 3.0 T data. Compared with eight clinicians, the 2D CNN model exhibited better diagnostic performance than the junior clinicians and was equivalent to senior clinicians. Conclusions The proposed 2D CNN model realized the adequate and efficient automatic diagnoses of STs, which achieved a comparable performance of junior musculoskeletal radiologists and orthopedic surgeons. It might be conducive to assisting poor-experienced radiologists, especially in community scenarios lacking consulting experts.

Prosthesis-associated infections are one of the main causes of implant failure; thus it is important to enhance the long-term antibacterial ability of orthopedic implants. Titanium dioxide nanotubes (TNTs) are biomaterials with good physicochemical properties and biocompatibility. Owing to their inherent antibacterial and drug-loading ability, the antibacterial application of TNTs has received increasing attention. In this review, the process of TNT anodizing fabrication is summarized. Also, the mechanism and the influencing factors of the antibacterial property of bare TNTs are explored. Furthermore, different antibacterial strategies for carrying drugs, as well as modifications to prolong the antibacterial effect and reduce drug-related toxicity are discussed. In addition, antibacterial systems based on TNTs that can automatically respond to infection are introduced. Finally, the currently faced problems are reviewed and potential solutions are proposed. This review provides new insight on TNT fabrication and summarizes the most advanced antibacterial strategies involving TNTs for the enhancement of long-term antibacterial ability and reduction of toxicity. Keywords: antibacterial property, drug delivery, titanium dioxide nanotube, orthopedic implant, surface modification

Background There is currently a lack of comprehensive prevalence information on arthritis and its various classifications among adults in the U.S., particularly given the notable absence of detailed data regarding the Asian population. We examined the trends in the prevalence of arthritis, including osteoarthritis (OA), rheumatoid arthritis (RA), psoriatic arthritis (PsA), and other types of arthritis, among U.S. adults by race between 2011 and 2018. Methods We analyzed data from the National Health and Nutrition Examination Survey (NHANES), spanning from 2011 to 2018. Our study focused on a nationally representative sample of U.S. adults aged 20 and older. Participants who answered “y es” to the research question “Doctors ever said you had arthritis?” were classified as having arthritis. Further classification into specific diseases was based on responses to the question “Which type of arthritis was it?” with options including “OA or degenerative arthritis, ” “RA, ” “PsA, ” or “Other. ” Results We analyzed 22,566 participants from NHANES (2011–2018), averaging 44.8 years, including 10,927 males. The overall arthritis prevalence rose significantly from 22.98% (95% CI: 21.47–24.55%) in 2011–12 to 27.95% (95% CI: 26.20–29.76%) in 2017–18 ( P for trend < 0.001). OA increased from 12.02% (95% CI: 10.82–13.35%) in 2011 to 14.93% (95% CI: 13.47–16.51%) in 2018 ( P for trend < 0.001). RA and PsA remained stable ( P for trend = 0.220 and 0.849, respectively), while other arthritis rose from 2.03% (95% CI: 1.54–2.67%) in 2011–12 to 3.14% (95% CI: 2.56–3.86%) in 2017–18 ( P for trend = 0.001). In Whites, Asians, and other races , arthritis and RA prevalence increased significantly ( P for trend < 0.05). OA and other arthritis rose in Whites and other races ( P for trend < 0.05), but no significant change occurred in the black population. The prevalence of PsA remained stable across all racial groups, with no statistically significant changes. Conclusions In this nationally representative U.S. adult survey spanning 2011 to 2018, we identified a rising prevalence trend in arthritis, OA, and other arthritis, with notable variations among different racial groups.

Previous studies have explored the role of the immune system in osteoporosis. This Mendelian randomization (MR) study further evaluated the causal relationship between 731 immune cell phenotypes and osteoporosis, exploring the mediating role of serum metabolites based on genetic prediction. Bidirectional two-sample Mendelian randomization was used to investigate the relationship between 731 immune cell phenotypes and osteoporosis. The 731 immune cell phenotypes, serum metabolites, and osteoporosis data used in this study were obtained from respective genome-wide association studies (GWAS). Inverse variable weighting (IVW) was used as the primary analysis method, and the P values were further corrected for false discovery rate (FDR). In addition, MR-Egger, weighted mode, simple mode, and weighted median analyses were performed to demonstrate the robustness of the results. In sensitivity analysis, the potential impact of horizontal pleiotropy was assessed by examining the intercept in MR-Egger regression, and the heterogeneity between SNPs was evaluated using Cochran's Q test, which was further supplemented with MR PRESSO analysis to detect pleiotropy. The analysis revealed significant associations between seven immune cell phenotypes and osteoporosis (OP). Furthermore, we identified several serum metabolites mediating immune cell phenotypes' effects on osteoporosis. For example, HLA DR++ monocyte %leukocyte promotes the occurrence of osteoporosis through the ratio of citrulline/dimethylarginine (SDMA + ADMA). Mediating effect ratios further elucidate the complex dynamics between immune cell phenotypic exposure, serum metabolites, and their combined effects on OP. We demonstrated the causal relationship between multiple immune cell phenotypes and osteoporosis through a bidirectional two-sample MR analysis. This study further elucidated the mediation effect of serum metabolites through mediation analysis, providing important insights into further understanding the pathogenesis of osteoporosis.

Background Hyperuricemia is associated with higher all-cause and cardiovascular mortality. However, the role of social determinants of health (SDoH) in this context remains unclear. This study aims to examine the relationship between SDoH, hyperuricemia, all-cause and cardiovascular mortality, and explore the mediating role of SDoH in these relationships. Methods This cohort study analyzed data from 23,919 US adults (aged ≥ 20) in the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2016, with linked mortality data through December 31, 2019. Two primary exposures were examined: hyperuricemia, defined as serum uric acid level > 420 µmol/L in males and > 360 µmol/L in females, and SDoH, which encompassed education level, marital status, income-to-poverty ratio (PIR), food security, health insurance, regular health-care access, housing instability, and employment. The primary outcomes were all-cause and cardiovascular mortality. Statistical methods included logistic regression, Cox proportional hazard model, and mediation analysis. Results The study cohort had a mean (SD) age of 49.27 (17.63) years, with 48.28% (95%Cl, 47.69%-48.86%) being male, and 68.52% (95%Cl, 65.27%-71.60%) identified as non-Hispanic White. Having three or more unfavorable SDoH significantly mediated the link between hyperuricemia and both all-cause and cardiovascular mortality. SDoH ≥ 6, SDoH = 5, SDoH = 4, and SDoH = 3 mediated 20.30% ( P  = 0.004), 13.94% ( P  = 0.044), 23.59% ( P  = 0.018), and 13.88% ( P  = 0.008) of the association between hyperuricemia and all-cause mortality, respectively. SDoH ≥ 6, SDoH = 5, SDoH = 4, and SDoH = 3 mediated 15.35% ( P  = 0.006), 14.87% ( P  = 0.050), 20.68% ( P  = 0.026), and 9.45% ( P  = 0.012) of the association between hyperuricemia and cardiovascular mortality. Conclusions SDoH significantly mediated the relationship between hyperuricemia and both all-cause and cardiovascular mortality.

This study aims to investigate the association between serum copper (Cu), selenium (Se), zinc (Zn), Se/Cu and Zn/Cu ratios and the risk of sarcopenia. In this study, which involved 2766 adults aged ≥ 20 years enrolled in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016, multivariable logistic regression, restricted cubic spline (RCS) models and mediation analyses were used. After full adjustment, multivariable logistic regression revealed that higher serum copper levels were correlated with an increased risk of sarcopenia. Conversely, higher serum Se/Cu (OR 0.45, 95% CI 0.23–0.89, P  = 0.023) and Zn/Cu (OR 0.49, 95% CI 0.27–0.90, P  = 0.024) were associated with a decreased risk of sarcopenia. The RCS curve indicated a non-linear, roughly inverted L-shaped relationship between serum Cu and sarcopenia risk ( P non-linear < 0.001). Additionally, Se/Cu ( P non-linear = 0.179) and Zn/Cu ( P non-linear = 0.786) showed negative linear associations with sarcopenia risk. Furthermore, white blood cell (WBC) count, neutrophil count, and systemic inflammation index (SII) were identified as significant mediators in the relationship between serum Cu and the risk of sarcopenia, with mediation proportions of 6.34%, 6.20%, and 4.37%, respectively (all P  < 0.05). Therefore, balancing essential trace metals is crucial for maintaining muscle health.

Objectives Socioeconomic factors significantly impact human health; however, the impact of exercise and income on musculoskeletal system health remains unclear. Our study aims to explore the relationship between exercise and income with musculoskeletal system health in young and middle-aged adults. Design This cross-sectional study used data from 7,515 adults aged 20–59 years, which were obtained from the US NHANES, 2011–2018. Participants’ musculoskeletal system health was evaluated on the basis of them having osteopenia, osteoporosis, or sarcopenia. Methods Ordinal regression was used to explore the correlation between income level, exercise volume, and musculoskeletal system health. Mediating effect analysis was used to assess whether the exercise volume affected the impact of income levels on musculoskeletal system health. Ordinal regression and restricted cubic spline curve were used to further analyze the relationship between exercise and income level. Results In the analysis of adjusted all covariates, the probability of having good musculoskeletal system health in high-income participants was higher than that of low- or middle-income participants. The probability of having good musculoskeletal system health in the actively exercising group higher than that of the participants exercised insufficiently or sufficiently. Mediating effect of exercise masked the effect of income on musculoskeletal system health. Participants with low income levels tended to spend more time exercising that those who had high income levels; exercise volume and income level had a significant non-linear relationship. Conclusion The findings presented will help identify young and middle-aged adults who are most at risk of developing musculoskeletal health problem and will likely benefit from certain lifestyle interventions.

Background The relationship between healthy lifestyle and frailty remains unclear. Healthy weight is crucial for overall well-being, but using body mass index (BMI) to evaluate weight management is inefficient. This study clarifies the association between healthy lifestyle or its factors (non-smoking, moderate drinking, healthy weight, healthy diet, sufficeint physical activity, and non-sedentary) and frailty, and the feasibility of using the weight-adjusted waist index (WWI) reflecting central obesity as an intermediate indicator. Methods This study included 4,473 participants from the 2007–2018 National Health and Nutrition Examination Survey (NHANES). Healthy lifestyle quality was assessed by summing the scores of each healthy lifestyle factor. Frailty was assessed using a 49-item frailty index (FI), categorizing participants into robust, pre-frail, and frail. Logistic regression to investigate the association between healthy lifestyle or its factors, WWI, and frailty. Smooth curve fitting and threshold effect analyses were used to elucidate the nonlinear association. Subgroup and two other sensitivity analyses were conducted to confirm the stability of the results. A causal mediation model examined the proportion of frailty mediated by WWI. Results The study identified 13.98% of the participants as frail. Optimal healthy lifestyle and frailty were negatively associated (OR: 0.39, 95%CI: 0.27–0.58). Five healthy lifestyle factors (non-smoking, healthy weight, healthy diet, sufficient physical activity, and non-sedentary) were associated with a lower prevalence of frailty, with odds ratios (OR) ranging from 0.48 to 0.61. We also analyzed the association between a healthy lifestyle and WWI (OR: 0.32, 95%CI: 0.27–0.37), WWI and frailty (OR: 1.85, 95%CI: 1.59–2.16). A positive association between WWI and FI was observed beyond the inflection point (9.99) (OR: 0.03, 95%CI: 0.02–0.03). Subgroup and sensitivity analyses confirmed stable associations between healthy lifestyle, WWI, and frailty. WWI partially mediated the association between a healthy lifestyle and frailty (mediating ratio = 20.50–20.65%). Conclusions An optimal healthy lifestyle and positive healthy lifestyle factors are associated with a lower incidence of frailty. WWI may mediate the relationship between a healthy lifestyle and frailty.

We examined the remains of an individual who was unearthed from the Tuchengzi site and was believed to be from the Warring States period in China. The remains exhibited segmental femoral fracture. We aimed to deduce the cause of fracture, medical interventions, healing process, and motion behavior after fracture healing using several techniques, including macroscopic observation, computed tomography (CT), and finite element analysis. Based on the morphology of the long bones, it appeared that the individual was male. The fractures resulted in an adduction angle of 5.47° and an anterior flexion angle of 21.34° in the proximal femur, while the femoral neck anteversion angle had been replaced by a retroversion angle of 10.74°. Additionally, the distal femur formed an abnormal anterior convex angle of 144.60°. CT revealed mature callus formation and visible trabecular bundles. The finite element analysis indicated that the maximum von Mises stress in the femur was 17.44 MPa during standing and 96.46 MPa during walking. We suggest that medical practitioners in the Warring States period possessed a good knowledge of thigh anatomy, enabling them to perform fracture reduction and fixation. Reasonable medical intervention facilitated fracture healing and load recovery. Satisfactory fracture healing ensured that the individual could engage in normal standing and walking activities after rehabilitation.