Microenvironmental interference with intra-articular stem cell regeneration influences the onset and progression of arthritis.

Studies have indicated that the preservation of joint health and the facilitation of damage recovery are predominantly contingent upon the joint's microenvironment, including cell-cell interactions, the extracellular matrix's composition, and the existence of local growth factors. Mesenchymal stem cells (MSCs), which possess the capacity to self-renew and specialize in many directions, respond to cues from the microenvironment, and aid in the regeneration of bone and cartilage, are crucial to this process. Changes in the microenvironment (such as an increase in inflammatory mediators or the breakdown of the extracellular matrix) in the pathological context of arthritis might interfere with stem cell activation and reduce their ability to regenerate. This paper investigates the potential role of joint microenvironmental variables in promoting or inhibiting the development of arthritis by influencing stem cells' ability to regenerate. The present status of research on stem cell activity in the joint microenvironment is also outlined, and potential directions for developing new treatments for arthritis that make use of these intervention techniques to boost stem cell regenerative potential through altering the intra-articular environment are also investigated. This review's objectives are to investigate these processes, offer fresh perspectives, and offer a solid scientific foundation for the creation of arthritic treatment plans in the future.

Exploring the impact of pathogenic microbiome in orthopedic diseases: machine learning and deep learning approaches.

Osteoporosis, arthritis, and fractures are examples of orthopedic illnesses that not only significantly impair patients' quality of life but also complicate and raise the expense of therapy. It has been discovered in recent years that the pathophysiology of orthopedic disorders is significantly influenced by the microbiota. By employing machine learning and deep learning techniques to conduct a thorough analysis of the disease-causing microbiome, we can enhance our comprehension of the pathophysiology of many illnesses and expedite the creation of novel treatment approaches. Today's science is undergoing a revolution because to the introduction of machine learning and deep learning technologies, and the field of biomedical research is no exception. The genesis, course, and management of orthopedic disorders are significantly influenced by pathogenic microbes. Orthopedic infection diagnosis and treatment are made more difficult by the lengthy and imprecise nature of traditional microbial detection and characterization techniques. These cutting-edge analytical techniques are offering previously unheard-of insights into the intricate relationships between orthopedic health and pathogenic microbes, opening up previously unimaginable possibilities for illness diagnosis, treatment, and prevention. The goal of biomedical research has always been to improve diagnostic and treatment methods while also gaining a deeper knowledge of the processes behind the onset and development of disease. Although traditional biomedical research methodologies have demonstrated certain limits throughout time, they nevertheless rely heavily on experimental data and expertise. This is the area in which deep learning and machine learning approaches excel. The advancements in machine learning (ML) and deep learning (DL) methodologies have enabled us to examine vast quantities of data and unveil intricate connections between microorganisms and orthopedic disorders. The importance of ML and DL in detecting, categorizing, and forecasting harmful microorganisms in orthopedic infectious illnesses is reviewed in this work.

A reprogrammable mechanical metamaterial with origami functional-group transformation and ring reconfiguration.

Recent advancements in reprogrammable metamaterials have enabled the development of intelligent matters with variable special properties in situ. These metamaterials employ intra-element physical reconfiguration and inter-element structural transformation. However, existing mono-characteristic homo-element mechanical metamaterials have limited reprogramming functions. Here, we introduce a reprogrammable mechanical metamaterial composed of origami elements with heterogeneous mechanical properties, which achieves various mechanical behavior patterns by functional group transformations and ring reconfigurations. Through the anisotropic assembly of two heterogeneous elements into a functional group, we enable mechanical behavior switching between positive and negative stiffness. The resulting polygonal ring exhibits rotational deformation, zero Poisson's ratio stretching/compression deformation, and negative Poisson's ratio auxetic deformation. Arranging these rings periodically yields homogeneous metamaterials. The reconfiguration of quadrilateral rings allows for continuous fine-tunability of the mechanical response and negative Poisson's ratio. This mechanical metamaterial could provide a versatile material platform for reprogrammable mechanical computing, multi-purpose robots, transformable vehicles and architectures at different scales.

Role of Mutual Diffusion in the Dissolution Behavior of One Primary Bulk Gas Nanobubble in Liquid: A Molecular Dynamics Study.

Dissolution of one primary bulk gas nanobubble in an undersaturated liquid constitutes one of the underlying issues of the exceptional stability of bulk gas nanobubble population. In this paper, the mutual diffusion coefficient at the gas-liquid interface of one primary bulk gas nanobubble is investigated via all-atom molecular dynamics simulation, and the applicability of the Epstein-Plesset theory is verified. The mutual diffusion coefficient, different from the self-diffusion coefficient in bulk gas or bulk liquid, is essentially determined by the chemical potential due to its driving role in the mass transfer across the interface. We could ascribe the low-rate dissolution of one primary bulk gas nanobubble in an undersaturated liquid to the slight attenuation of the mutual diffusion coefficient at the interface. The results show that the dissolution process of one primary bulk gas nanobubble in an undersaturated liquid fundamentally obeys the Epstein-Plesset theory and that the macroscopic dissolution rate is intrinsically determined by the gas mutual diffusion coefficient at the interface rather than the self-diffusion coefficient in the bulk phase. The mass transfer viewpoint from the present study might actively promote subsequent studies on the super-stability of bulk gas nanobubble population in liquid.

Comparison of the Effect and Complications of Sequential Bilateral Arthroplasty at Different Time Intervals and Simultaneous Bilateral Total Knee Arthroplasty: A Single-Centre Retrospective Cohort Study.

INTRODUCTION: To the authors' knowledge, there is no current consensus regarding the optimal interprocedural interval for patients who have undergone bilateral total knee arthroplasty (BTKA). The purpose of this study is to evaluate complication rates and functional outcome in patients who have undergone BTKA (simultaneous or sequential at different time intervals), and to determine an optimal time frame for the second knee. METHODS: Data from 315 patients who were able to tolerate simultaneous BTKA according to the anaesthesiologist's preoperative assessment between 2016 and 2020 were analysed retrospectively. According to the operative time interval, they were divided into simultaneous, ≤ 1-month sequential, 1- to 3-month sequential, and ≥ 3-month sequential BTKA groups. The primary outcomes were revision and readmission rates during the follow-up period, and the secondary outcomes were hospital length of stay (LOS), transfusion and postoperative complications. RESULTS: There was no difference in the implant survival or readmission rate between the groups (p > 0.05). Multivariable linear regression showed that interprocedural interval and body mass index (BMI) affected LOS; the LOS of simultaneous BTKA was the shortest (p < 0.05). BMI was associated with an increased LOS of 0.25 days (95% CI 0.02-0.48, p = 0.03). A modified Poisson regression model showed that the odds of blood transfusion were reduced in sequential BTKAs of any interval (p < 0.05), and preoperative haemoglobin (Hb) was also a risk factor (RR 0.96, 95% CI 0.95-0.98, p < 0.001). The interprocedural interval was not a risk factor for postoperative cardiovascular and cerebrovascular complications. CONCLUSION: For appropriate patients, simultaneous BTKA is beneficial. However, higher preoperative haemoglobin was required to mitigate the high blood transfusion rate associated with simultaneous surgeries. If suitable patients refuse simultaneous BTKA for other non-medical reasons, sequential BTKA with an interval greater than 1 month is recommended.

Apremilast prevents IL­17­induced cellular senescence in ATDC5 chondrocytes mediated by SIRT1.

Osteoarthritis is the most prevalent joint degenerative disease and has been considered a major cause of severe joint pain and physical disability in the elderly. The chondrocyte is the only cell type found in articular cartilage and chondrocyte senescence plays a pivotal role in the pathogenesis of osteoarthritis. Apremilast is an oral PDE4 inhibitor and has been used for the treatment of patients with active psoriatic arthritis. In the present study, the biological function of apremilast was examined in an interleukin (IL)­17­treated chondrocyte model. Expression levels of target genes and proteins were measured using reverse transcription­quantitative PCR, ELISA, and western blotting, respectively. ROS levels in chondrocytes were examined using the fluorescent dye DCFH­DA. Cellular senescence was determined using senescence-associated-ß-galactosidase staining. The profile of cell cycle phases was analyzed via flow cytometry. It was revealed that treatment with apremilast reduced the expression of IL­1ß, MCP­1, and the production of ROS. SA­ß­gal staining results indicated that the presence of apremilast suppressed IL­17­induced cellular senescence. Furthermore, apremilast prevented IL­17­induced G0/G1 phase cell cycle arrest. In addition, it was demonstrated that apremilast suppressed IL­17­induced expression of p21 and PAI­1. Notably, the silencing of sirtuin 1 (SIRT1) abolished the protective effect of apremilast against IL­17­induced cellular senescence, suggesting that the action of apremilast in chondrocytes is dependent on SIRT1. In conclusion, the present results revealed that apremilast exerted a beneficial effect, thereby protecting chondrocytes from senescence induced by IL­17.

Thymoquinone reduces spinal cord injury by inhibiting inflammatory response, oxidative stress and apoptosis via PPAR-γ and PI3K/Akt pathways.

The present study used a mild contusion injury in rat spinal cord to determine that thymoquinone reduces inflammatory response, oxidative stress and apoptosis in a spinal cord injury (SCI) rat model and to demonstrate its possible molecular mechanisms. The rats in the thymoquinone group received 30 mg/kg thymoquinone once daily by intragastric administration from 3 weeks after surgery. Hematoxylin and eosin staining, Basso, Beattie and Bresnahan (BBB) scale and tissue water content detection were used in the present study to analyze the effect of thymoquinone on SCI. The activity of inflammatory response mediators, oxidative stress factors and caspase-3/9 was measured using ELISA kits. Furthermore, western blotting was performed to analyzed the protein expression levels of prostaglandin E2, suppressed cyclooxygenase-2 (COX-2) and activated peroxisome proliferator-activated receptor γ (PPAR-γ), PI3K and Akt. The results from the study demonstrated that thymoquinone increased Basso, Beattie and Bresnahan score and decreased water content in spinal cord tissue. Treatment with thymoquinone decreased inflammatory response [measured by levels of tumor necrosis factor α, interleukin (IL)-1ß, IL-6 and IL-18], oxidative stress (measured by levels of superoxide dismutase, catalase, glutathione and malondialdehyde) and cell apoptosis (measured by levels of caspase-3 and caspase-9) in SCI rats. Thymoquinone treatment inhibited prostaglandin E2 activity, suppressed COX-2 protein expression and activated PPAR-γ, PI3K and p-Akt protein expression in SCI rats. These data revealed that thymoquinone reduces inflammatory response, oxidative stress and apoptosis via PPAR-γ and PI3K/Akt pathways in an SCI rat model.

Critical ratio between the amplitudes of two overtaking solitary water waves.

In this paper, we study the critical ratio between the amplitudes of two overtaking solitary waves on a layer of water with uniform depth. At the center of encounter, the wave profile is fore-and-aft symmetric, but it could have a single peak or double peaks. The critical ratio separates these two regimes. At the critical point, the wave peak is flat with zero slope and curvature. We solve the full water wave problem numerically by using a fully nonlinear and highly dispersive Boussinesq model. The model is numerically justified to be a good approximation of the Euler equations for solitary waves with very large amplitude. For small amplitude water waves, our calculated critical ratio reduces to the well-known result of 3 predicted by the Korteweg-de Vries equation, a weakly nonlinear and weakly dispersive model. For large amplitude water waves, the nonlinear effect is significant; we find that the critical ratio deviates significantly from 3. For water waves with very high amplitude, e.g., 0.6 relative wave height, the critical ratio could be as large as 4. Our result suggests that higher-order nonlinear and dispersive effects are important when modeling the strong interaction between large amplitude water waves.