The number of orthopedic implants for bone fixation and joint arthroplasty has been steadily increasing over the past few years. However, implant-associated infection (IAI), a major complication in orthopedic surgery, impacts the quality of life and causes a substantial economic burden on patients and societies. While research and study on IAI have received increasing attention in recent years, the failure rate of IAI has still not decreased significantly. This is related to microbial biofilms and their inherent antibiotic resistance, as well as the various mechanisms by which bacteria evade host immunity, resulting in difficulties in diagnosing and treating IAIs. Hence, a better understanding of the complex interactions between biofilms, implants, and host immunity is necessary to develop new strategies for preventing and controlling these infections. This review first discusses the challenges in diagnosing and treating IAI, followed by an extensive review of the direct effects of orthopedic implants, host immune function, pathogenic bacteria, and biofilms. Finally, several promising preventive or therapeutic alternatives are presented, with the hope of mitigating or eliminating the threat of antibiotic resistance and refractory biofilms in IAI.

The prevalence and role of malnutrition in periprosthetic joint infection (PJI) remain unclear. This study aimed to use measurable nutritional screening tools to assess the prevalence of malnutrition in PJI patients during two-stage exchange arthroplasty and to explore the association between malnutrition and treatment failure. Our study retrospectively included 183 PJI cases who underwent 1st stage exchange arthroplasty and had available nutritional parameters, of which 167 proceeded with 2nd stage reimplantation. The recently proposed Musculoskeletal Infection Society (MSIS) Outcome Reporting Tool was used to determine clinical outcomes. The Controlling Nutritional Status (CONUT), Nutritional Risk Index (NRI), and Naples Prognostic Score (NPS) were used to identify malnutrition at 1st and 2nd stage exchange, respectively. Multivariate logistic regression analyses were performed to determine the association between malnutrition and treatment failure. Restricted cubic spline models were further used to explore the dose–response association. Additionally, risk factors for moderate-to-severe malnutrition were evaluated. Malnourished patients identified by CONUT, NPS, and NRI accounted for 48.1% (88/183), 98.9% (181/183), and 55.7% (102/183) of patients at 1st stage, and 9.0% (15/167), 41.9% (70/167), and 43.1% (72/167) at 2nd stage, indicating a significant improvement in nutritional status. We found that poorer nutritional status was a predictor of treatment failure, with CONUT performing best as a predictive tool. Moderate-to-severe malnutrition at 1st stage identified by CONUT was significantly related to treatment failure directly caused by PJI (odds ratio [OR] = 5.86), while the OR was raised to 12.15 at 2nd stage (OR = 12.15). The linear dose–response associations between them were also confirmed (P for nonlinearity at both 1st and 2nd stage > 0.05). As for total treatment failure, moderate-to-severe malnutrition as determined by CONUT was associated with a 1.96-fold and 8.99-fold elevated risk at the 1st and 2nd stages, respectively. Age ≥ 68 years (OR = 5.35) and an increased number of previous surgeries (OR = 2.04) may be risk factors for moderate-to-severe malnutrition. Overall, the prevalence of malnutrition in PJI patients is very high. Given the strong association between moderate-to-severe malnutrition identified by CONUT and PJI treatment failure, COUNT could be a promising tool to evaluate the nutritional status of PJI patients to optimize treatment outcomes.

The therapeutic potential of targeting CD4+Foxp3+ regulatory T cells (Tregs) remains controversial under the condition of neuroinflammation. This study aims to explore the neuroprotective role of Tregs in optic nerve ischemia (ONI) and evaluate the therapeutic strategy of Tregs transfer with a focus on targeting the mammalian target of rapamycin (mTOR) pathway. Intraocular pressure was transiently increased in adult C57BL/6 mice to induce ONI. Mucosal tolerance of myelin basic protein (MBP) markedly increased retinal ganglion cell (RGC) survival after ONI through enhanced Tregs suppression. mTOR inhibition significantly promoted the frequency of MBP-immunized Tregs in vitro with increased production of anti-inflammatory cytokines. Transient rapamycin treatment highly promoted the immunosuppressive capacity of Tregs and inhibited retinal inflammation in ONI animals. Intravenous infusion of MBP-immunized Tregs, instead of regular Tregs, beneficially modulated immune activities of host retinal CD11b+ cells and CD4+ effector T cells, leading to significant improvement of RGC survival. Importantly, rapamycin treatment further enhanced the neuroprotective effect of Tregs transfer. Taken together, these findings reveal a fine regulation of mTOR signaling on immunized Tregs after acute retinal injury. Adoptive transfer with targeting-mTOR strategy markedly improves neuronal recovery after ONI, supporting the therapeutic potentials of Tregs in acute and chronic neurological disorder.

Background: Artificial intelligence (AI) has promising applications in arthroplasty. In response to the knowledge explosion resulting from the rapid growth of publications, we applied bibliometric analysis to explore the research profile and topical trends in this field. Methods: The articles and reviews related to AI in arthroplasty were retrieved from 2000 to 2021. The Java-based Citespace, VOSviewer, R software-based Bibiometrix, and an online platform systematically evaluated publications by countries, institutions, authors, journals, references, and keywords. Results: A total of 867 publications were included. Over the past 22 years, the number of AI-related publications in the field of arthroplasty has grown exponentially. The United States was the most productive and academically influential country. The Cleveland Clinic was the most prolific institution. Most publications were published in high academic impact journals. However, collaborative networks revealed a lack and imbalance of inter-regional, inter-institutional, and inter-author cooperation. Two emerging research areas represented the development trends: major AI subfields such as machine learning and deep learning, and the other is research related to clinical outcomes. Conclusion: AI in arthroplasty is evolving rapidly. Collaboration between different regions and institutions should be strengthened to deepen our understanding further and exert critical implications for decision-making. Predicting clinical outcomes of arthroplasty using novel AI strategies may be a promising application in this field.

Background: Pregnant women are highly susceptible to periodontal disease due to changes in hormonal and immune levels, which places a huge burden on the healthcare system and requires multidisciplinary interventions. This study aimed to assess the scientific profile and research trends related to periodontal disease in pregnancy through a bibliometric approach. Methods: Publications about periodontal disease in pregnancy from 2000 to 2022 were extracted from Science Citation Index Expanded. The knowledge networks of countries, institutions, authors, journals, references, and keywords in this field were constructed using the Citespace, VOSviewer, Bibliometrix, and BIBLIOMETRIC.COM platforms. Furthermore, correlations between the characteristics of countries and the number or impact of publications were analyzed. Results: 1162 original studies and reviews were included. There was a trend toward increased publications and citations in this field. The United States had the highest academic productivity and impact by a significant margin, while correlation analyses indicated that economic power may correlate with national scientific activity. The University of North Carolina and Offenbacher S were the most influential institution and author, respectively, taking center stage in the collaborative networks. However, only several loose connections between countries or institutions were identified in the global collaborative network analysis. Six of the top ten most productive journals were in Q1 in the Journal Citation Report, and there was intensive interaction between different research subfields, such as immunology, molecular biology, and microbiology. Frontier topics were primarily clustered in two areas: (1) oral microbiology, such as microbiome, oral bacteria, and Fusobacterium nucleatum; and (2) public health, such as quality of life, pregnancy outcomes, oral health, obesity, and classification. Conclusion: Since 2000, periodontal disease in pregnancy is receiving increasingly widespread attention and is rapidly evolving at a multidisciplinary level. Oral microbiological pathogenesis and public health impact-related research deserve more exploration and may be the future direction of research. Enhanced Collaboration and interdisciplinary communication may further facilitate progress in this discipline.