Xiaomeng Zhang

The global epidemiological landscape of diseases attributable to diet low in vegetables remains insufficiently characterized. This study aims to provide a comprehensive assessment of the disease burden associated with this risk on a global scale. Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021, the summary exposure value (SEV) of diet low in vegetables and the associated burden from 1990 to 2021 were analyzed. Trends of deaths and disability‐adjusted life years (DALYs) attributed to diet low in vegetables were measured using the age‐standardized rate (ASR) and the estimated annual percentage change (EAPC). The relationship between health outcomes and the Socio‐demographic Index (SDI) was explored to identify structural inequalities. Globally, the SEV attributable to diet low in vegetables was 27.34 (95% UI: 17.17–32.91) in 2021. Between 1990 and 2021, the SEV showed a continuous decline, with an EAPC of −0.72 (95% CI: −0.84 to −0.60). Central Sub‐Saharan Africa had the highest SEVs of diet low in vegetables, while East Asia had the lowest. The rates of deaths and DALYs attributed to diet low in vegetables have consistently decreased between 1990 and 2021. The EAPC for age‐standardized mortality rate (ASMR) was −2.01 (95% CI: −2.12 to −1.88), and the EAPC for age‐standardized DALY rate (ASDR) was −2.06 (95% CI: −2.21 to −1.91). For both deaths and DALYs, males consistently had higher numbers and rates than females. Furthermore, regions with lower SDIs faced a greater burden compared to higher SDI counterparts. Globally, cardiovascular diseases constituted the primary component of the burden associated with this dietary risk, followed by diabetes and kidney diseases. Although the global burden attributable to a diet low in vegetables has decreased, intake levels continue to vary across regions. These findings provide a descriptive foundation for identifying high‐risk populations.

Engineering of microcarriers with tailored properties is a pivotal challenge in developing physiologically relevant three-dimensional (3D) in vitro tumor models, which are emerging as critical tools in cancer research. This study developed alginate-zein (AZ) composite microcarriers with tuned mechanical properties via a tailored microfluidic device for constructing in vitro 3D osteosarcoma models. A co-axial capillary microfluidic device was prepared to generate AZ microcarriers, and the ratio of calcium alginate to zein was varied. MG-63 were cultured on the microcarriers to obtain proposed osteosarcoma models. Intracellular reactive oxygen species (ROS) levels of these cells were quantified, and qRT-PCR analysis was conducted to examine the expression of genes associated with proliferation, apoptosis, migration, and invasion, along with other promalignancy markers. Doxorubicin was used to validate the utility of this model for drug screening. It was shown that AZ microcarriers were of high uniformity and monodispersity. Cell-microcarrier constructs were formed after MG-63 being cultured on these microcarriers, which further exhibited upregulated intracellular ROS levels and elevated expression of vegf, vim, cdh-2 (n-cadherin), and runx2, alongside downregulated cdh-1 (e-cadherin) expression. The expression of these promalignant markers and observed enhancement in drug resistance by cells within the constructs demonstrated the successful establishment of the expected osteosarcoma model and its application for drug screening. AZ-β microcarriers with a relative zein portion of 9:1 and an elastic modulus of 159.73 kPa were the optimal microcarrier for establishing the osteosarcoma model. This study presented a robust methodology for establishing 3D in vitro tumor models for developing therapeutic intervention.

Neutrophils, as first-line immune cells, typically lose their edge within the diabetic wounds accompanied by methicillin-resistant Staphylococcus aureus (MRSA) infections (the D/M setting), playing the role of "more foe than friend" during the healing process. Specifically, reduced influx of calcium ions (Ca²⁺) and impaired calcium homeostasis yield the dysfunction of neutrophil sequential behaviors in pathogen killing and wound healing, manifesting as suppressed chemotaxis, decreased intracellular reactive oxygen species (ROS) generation, prolonged apoptosis, and retention of neutrophil extracellular traps (NETs). To address this challenge, this study fabricated potassium (K)-doped manganese dioxide nanoparticles (MnO₂ NPs), which activated transmembrane Ca²⁺ channels by inducing neutrophil depolarization via electron transfer. Subsequently, this contributed to the initial Ca²⁺ influx and reprogrammed Ca²⁺-dependent behaviors of impaired neutrophils. Also, the potential antimicrobial capacity of K-MnO₂ NPs created a favorable extracellular environment that restored calcium homeostasis, enabling apoptotic neutrophils to be removed timely. Therefore, the wounds treated with K-MnO₂ NPs in the D/M setting exhibited potent resistance to MRSA and rapid healing, which could be attributed to the synergistic effects of K-MnO₂ NPs in leveraging Ca²⁺ influx and maintaining calcium homeostasis. In brief, K-MnO₂ NPs constitute an effective strategy to resist MRSA and rapid wound healing in the D/M setting.

Local immunoinflammatory events instruct skeletal stem cells (SSCs) to repair/regenerate bone after injury, but mechanisms are incompletely understood. We hypothesized that specialized Tregs are necessary for bone repair and interact directly with SSCs through organ-specific messages. Both in human patients with bone fracture and a mouse model of bone injury, we identified a bone injury–responding Treg subpopulation with bone-repair capacity marked by CCR8. Local production of CCL1 induced a massive migration of CCR8 ⁺ Tregs from periphery to the injury site. Depending on secretion of progranulin (PGRN), a protein encoded by the granulin ( Grn ) gene, CCR8 ⁺ Tregs supported the accumulation and osteogenic differentiation of SSCs and thereby bone repair. Mechanistically, we revealed that CCL1 enhanced expression levels of basic leucine zipper ATF-like transcription factor (BATF) in CCR8 ⁺ Tregs, which bound to the Grn promoter and increased Grn translational output and then PGRN secretion. Together, our work provides a new perspective in osteoimmunology and highlights possible ways of manipulating Treg signaling to enhance bone repair and regeneration.

Excessive production of reactive oxygen species (ROS) around titanium implants under diabetic conditions causes persistent inflammation, leading to poor osseointegration and even implant failure. Surface modification is an effective way to promote ROS clearance, alleviate inflammation, and stimulate bone formation. In this study, a multifunctional coating is fabricated by introducing cerium (Ce)-containing mesoporous bioactive glass nanoparticles (Ce-MBGNs) onto the titanium surface via an electrophoretic deposition method. The incorporation of Ce-MBGNs remarkably improves surface hydrophilicity by increasing the surface areas. The bioactive ions are appropriately released, thereby promoting mesenchymal stem cell proliferation and differentiation under diabetic conditions. The conversion between Ce(III) and Ce(IV) endows Ce-MBGNs coating with antioxidative nanoenzymes properties to scavenge diabetes-induced ROS, resulting in macrophage polarization towards the anti-inflammatory phenotype. The therapeutic effect of Ce-MBGNs-modified titanium implants is also verified in diabetic rats by inhibiting inflammatory responses and accelerating early osseointegration. Taken together, the findings reveal that the ROS-scavenging and immunomodulation activity of the Ce-MBGNs coating contributes to enhanced osseointegration, and provides a novel implant surface for diabetic patients.

Background: While large language models (LLMs) such as ChatGPT and Google Bard have shown significant promise in various fields, their broader impact on enhancing patient health care access and quality, particularly in specialized domains such as oral health, requires comprehensive evaluation. Objective: This study aims to assess the effectiveness of Google Bard, ChatGPT-3.5, and ChatGPT-4 in offering recommendations for common oral health issues, benchmarked against responses from human dental experts. Methods: This comparative analysis used 40 questions derived from patient surveys on prevalent oral diseases, which were executed in a simulated clinical environment. Responses, obtained from both human experts and LLMs, were subject to a blinded evaluation process by experienced dentists and lay users, focusing on readability, appropriateness, harmlessness, comprehensiveness, intent capture, and helpfulness. Additionally, the stability of artificial intelligence responses was also assessed by submitting each question 3 times under consistent conditions. Results: Google Bard excelled in readability but lagged in appropriateness when compared to human experts (mean 8.51, SD 0.37 vs mean 9.60, SD 0.33; P=.03). ChatGPT-3.5 and ChatGPT-4, however, performed comparably with human experts in terms of appropriateness (mean 8.96, SD 0.35 and mean 9.34, SD 0.47, respectively), with ChatGPT-4 demonstrating the highest stability and reliability. Furthermore, all 3 LLMs received superior harmlessness scores comparable to human experts, with lay users finding minimal differences in helpfulness and intent capture between the artificial intelligence models and human responses. Conclusions: LLMs, particularly ChatGPT-4, show potential in oral health care, providing patient-centric information for enhancing patient education and clinical care. The observed performance variations underscore the need for ongoing refinement and ethical considerations in health care settings. Future research focuses on developing strategies for the safe integration of LLMs in health care settings.

Gingival inflammation and alveolar bone loss are characteristic manifestations of periodontitis. Interleukin (IL)-1β, the maturation of which is mainly regulated by NOD-like receptor protein (NLRP) 3 inflammasome, not only amplifies the inflammatory response but also triggers osteoclastogenesis, thereby accelerating the progression of periodontitis. Dioscin, a natural steroid saponin, has been shown to inhibit NLRP3 inflammasome. Nevertheless, research on the effectiveness of Dioscin for the management of periodontitis remains scarce. In this study, Dioscin was found to dramatically reduce the integral components of NLRP3 inflammasome, ultimately limiting IL-1β secretion. Notably, the inhibitory impact of Dioscin on NLRP3 inflammasome might be exerted by curbing the generation of mitochondrial (mt) reactive oxygen species (ROS) and oxidized (ox) mtDNA, which were mediated by inhibition of K⁺ efflux. Furthermore, Dioscin effectively alleviated periodontitis in mice. Overall, the results established that Dioscin could alleviate periodontitis by inhibiting NLRP3 inflammasome via modulation of the K⁺ efflux-mtROS-ox-mtDNA pathway, holding the potential to treat periodontitis and other NLRP3-driven inflammatory diseases.

BACKGROUND While large language models (LLMs) such as ChatGPT and Google Bard have shown significant promise in various fields, their broader impact on enhancing patient health care access and quality, particularly in specialized domains such as oral health, requires comprehensive evaluation. OBJECTIVE This study aims to assess the effectiveness of Google Bard, ChatGPT-3.5, and ChatGPT-4 in offering recommendations for common oral health issues, benchmarked against responses from human dental experts. METHODS This comparative analysis used 40 questions derived from patient surveys on prevalent oral diseases, which were executed in a simulated clinical environment. Responses, obtained from both human experts and LLMs, were subject to a blinded evaluation process by experienced dentists and lay users, focusing on readability, appropriateness, harmlessness, comprehensiveness, intent capture, and helpfulness. Additionally, the stability of artificial intelligence responses was also assessed by submitting each question 3 times under consistent conditions. RESULTS Google Bard excelled in readability but lagged in appropriateness when compared to human experts (mean 8.51, SD 0.37 vs mean 9.60, SD 0.33; P=.03). ChatGPT-3.5 and ChatGPT-4, however, performed comparably with human experts in terms of appropriateness (mean 8.96, SD 0.35 and mean 9.34, SD 0.47, respectively), with ChatGPT-4 demonstrating the highest stability and reliability. Furthermore, all 3 LLMs received superior harmlessness scores comparable to human experts, with lay users finding minimal differences in helpfulness and intent capture between the artificial intelligence models and human responses. CONCLUSIONS LLMs, particularly ChatGPT-4, show potential in oral health care, providing patient-centric information for enhancing patient education and clinical care. The observed performance variations underscore the need for ongoing refinement and ethical considerations in health care settings. Future research focuses on developing strategies for the safe integration of LLMs in health care settings.

With the rapid development of implantable biomaterials, the rising risk of bacterial infections has drawn widespread concern. Due to the high recurrence rate of bacterial infections and the issue of antibiotic resistance, the common treatments of peri-implant infections cannot meet the demand. In this context, stimuli-responsive biomaterials have attracted attention because of their great potential to spontaneously modulate the drug releasing rate. Numerous smart bacteria-responsive drug delivery systems (DDSs) have, therefore, been designed to temporally and spatially release antibacterial agents from the implants in an autonomous manner at the infected sites. In this review, we summarized recent advances in bacteria-responsive DDSs used for combating bacterial infections, mainly according to the different trigger modes, including physical stimuli-responsive, virulence-factor-responsive, host-immune-response responsive and their combinations. It is believed that the smart bacteria-responsive DDSs will become the next generation of mainstream antibacterial therapies.