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The osteo-immunomodulatory properties of biomaterials play an important role in the outcomes of bone regeneration. Graphene oxide (GO) has been widely applied in many research fields due to its unique properties. However, the immunomodulatory properties of GO as a biomaterial for bone tissue engineering are still unclear. In this study, we evaluated the Inflammatory response of RAW264.7 cells influenced by GO. Then the osteogenic differentiation of BMSCs, and angiogenic differentiation of human umbilical vein endothelial cells (HUVECs) by stimulation with GO/RAW 264.7-conditioned culture medium were accessed. We also further investi gated the possible mechanisms underlying the osteo- and angio-immunomodulatory effects of GO. Our results showed that GO stimulates the secretion of oncostatin M, tumor necrosis factor alpha and other factors through the nuclear factor-κB pathway. GO/RAW264.7-conditioned medium promoted the osteogenic differentiation of BMSCs, stimulated upregulation of the HUVECs of vascular-related receptors, and promoted their tube formation in vitro. In conclusion, our research shows that GO, as a biomaterial, can induce the formation of a beneficial osteo-immunomodulatory environment and is a promising biomaterial for bone tissue engineering.

Iron oxide nanoparticles (IONPs) have been employed for hyperthermia treatments, stem cell therapies, cell labeling, and imaging modalities. The biocompatibility and cytotoxic effects of iron oxide nanoparticles when used in biomedical applications, however, are an ongoing concern. Endothelial cells have a critical role in this research dealing with tumors, cardiovascular disease and inflammation. However, there is little information dealing with the biologic effects of IONPs on the endothelial cell. This paper deals with the influence of dextran and citric acid coated IONPs on the behavior and function of human umbilical vein endothelial cells (HUVECs). After exposing endothelial cells to IONPs, dose-dependent effects on HUVECs viability, cytoskeleton and function were determined. Both citric acid and dextran coated particles appeared to be largely internalized by HUVECs through endocytosis and contribute to eventual cell death possibly by apoptosis. Cytoskeletal structures were greatly disrupted, as evidenced by diminished vinculin spots, and disorganized actin fiber and tubulin networks. The capacity of HUVECs to form a vascular network on Matrigel™ diminished after exposure to IONPs. Cell migration/invasion were inhibited significantly even at very low iron concentrations (0.1 mM). The results of this study indicate the great importance of thoroughly understanding nanoparticle-cell interactions, and the potential to exploit this understanding in tumor therapy applications involving IONPs as thermo/chemoembolization agents.

Rib fracture detection is time-consuming and demanding work for radiologists. This study aimed to introduce a novel rib fracture detection system based on deep learning which can help radiologists to diagnose rib fractures in chest computer tomography (CT) images conveniently and accurately. A total of 1707 patients were included in this study from a single center. We developed a novel rib fracture detection system on chest CT using a three-step algorithm. According to the examination time, 1507, 100 and 100 patients were allocated to the training set, the validation set and the testing set, respectively. Free Response ROC analysis was performed to evaluate the sensitivity and false positivity of the deep learning algorithm. Precision, recall, F1-score, negative predictive value (NPV) and detection and diagnosis were selected as evaluation metrics to compare the diagnostic efficiency of this system with radiologists. The radiologist-only study was used as a benchmark and the radiologist-model collaboration study was evaluated to assess the model’s clinical applicability. A total of 50,170,399 blocks (fracture blocks, 91,574; normal blocks, 50,078,825) were labelled for training. The F1-score of the Rib Fracture Detection System was 0.890 and the precision, recall and NPV values were 0.869, 0.913 and 0.969, respectively. By interacting with this detection system, the F1-score of the junior and the experienced radiologists had improved from 0.796 to 0.925 and 0.889 to 0.970, respectively; the recall scores had increased from 0.693 to 0.920 and 0.853 to 0.972, respectively. On average, the diagnosis time of radiologist assisted with this detection system was reduced by 65.3 s. The constructed Rib Fracture Detection System has a comparable performance with the experienced radiologist and is readily available to automatically detect rib fracture in the clinical setting with high efficacy, which could reduce diagnosis time and radiologists’ workload in the clinical practice.

Matrix metalloproteinase 2 (MMP2) is a well-characterized protein that is indispensable for extracellular matrix remodeling and other pathological processes, such as tumor progression and skeletal dysplasia. Excessive activation of MMP2 promotes osteolytic metastasis and bone destruction in late-stage cancers, while its loss-of-function mutations result in the decreased bone mineralization and generalized osteolysis occurring progressively in skeletal developmental disorders, particularly in multicentric osteolysis, nodulosis and arthropathy (MONA). Either upregulation or downregulation of MMP2 activity can result in the same osteolytic effects. Thus, different functions of MMP2 have been recently identified that could explain this observation. While MMP2 can degrade bone matrix, facilitate osteoclastogenesis and amplify various signaling pathways that enhance osteolysis in bone metastasis, its role in maintaining the number of bone cells, supporting osteocytic canalicular network formation and suppressing leptin-mediated inhibition of bone formation has been implicated in osteolytic disorders caused by MMP2 deficiency. Furthermore, the proangiogenic activity of MMP2 is one of the potential mechanisms that are associated with both pathological situations. In the present article, the latest research on MMP2 in bone homeostasis is reviewed and the mechanisms underlying the role of this protein in skeletal metastasis and developmental osteolysis are discussed.

Identifying patients with non-small cell lung cancer (NSCLC) who are optimal candidates for immunotherapy is a cornerstone in clinical decision-making. The tumor immune microenvironment (TIME) is intricately linked with both the prognosis of the malignancy and the efficacy of immunotherapeutic interventions. CD8+ T cells, and more specifically, tissue-resident memory CD8+ T cells [CD8+ tissue-resident memory T (TRM) cells] are postulated to be pivotal in orchestrating the immune system's assault on tumor cells. Nevertheless, the accurate quantification of immune cell infiltration-and by extension, the prediction of immunotherapeutic efficacy-remains a significant scientific frontier. In this study, we introduce a cutting-edge non-invasive radiomic model, grounded in TIME markers (CD3+ T, CD8+ T, and CD8+ TRM cells), to infer the levels of immune cell infiltration in NSCLC patients receiving immune checkpoint inhibitors and ultimately predict their response to immunotherapy. Data from patients who had surgical resections (cohort 1) were employed to construct a radiomic model capable of predicting the TIME. This model was then applied to forecast the TIME for patients under immunotherapy (cohort 2). Conclusively, the study delved into the association between the predicted TIME from the radiomic model and the immunotherapeutic outcomes of the patients. For the immune cell infiltration radiomic prediction models in cohort 1, the AUC values achieved 0.765, 0.763, and 0.675 in the test set of CD3+ T, CD8+ T, and CD8+ TRM, respectively. While the AUC values for the TIME-immunotherapy predictive value were 0.651, 0.763, and 0.829 in the CD3-immunotherapy response model, CD8-immunotherapy response model, and CD8+ TRM-immunotherapy response model in cohort 2, respectively. The CD8+ TRM-immunotherapy model exhibited the highest predictive value and was significantly better than the CD3-immunotherapy model in predicting the immunotherapy response. The progression-free survival (PFS) analysis based on the predicted levels of CD3+ T, CD8+ T, and CD8+ TRM immune cell infiltration showed that the CD8+ T cell infiltration level was an independent factor (P=0.014, HR=0.218) with an AUC value of 0.938. Our empirical evidence reveals that patients with substantial CD8+ T cell infiltration experience a markedly improved PFS compared with those with minimal infiltration, asserting the status of the CD8+ T cell as an independent prognosticator of PFS in the context of immunotherapy. Although CD8+ TRM cells demonstrated the greatest predictive accuracy for immunotherapy response, their predictive strength for PFS was marginally surpassed by that of CD8+ T cells. These insights advocate for the application of the proposed non-invasive radiomic model, which utilizes TIME analysis, as a reliable predictor for immunotherapy outcomes and PFS in NSCLC patients.

Background The incidence of checkpoint inhibitor-associated pneumonitis (CIP) in advanced non-small cell lung cancer (NSCLC) has been substantiated through large-scale clinical trials or real-world studies. However, reports on CIP incidence within the context of neoadjuvant immunotherapy for resectable NSCLC remain scarce. This study endeavors to investigate the incidence, risk factors, and outcomes of CIP in patients with resectable NSCLC receiving neoadjuvant immunochemotherapy. Methods A retrospective, case-control study was conducted on patients diagnosed with NSCLC stages IIA–IIIB who received neoadjuvant immunochemotherapy between January 2018 and September 2022. Patients were stratified into two groups based on the presence or absence of CIP, facilitating a comparative analysis of clinical characteristics, treatment modalities, physiological indicators, and prognostic outcomes . Results The study cohort comprised 245 patients, with 11.4% (28/245) experiencing CIP. The median period of CIP onset was 70 (range, 40–221) days. The incidence of severe CIP (grade 3–4) was 3.7% (9/245). Patients with CIP showed a higher all-cause mortality rate of 21.4% (6/28) compared to that of patients without CIP. Those who developed CIP exhibited elevated body mass index (BMI) values ( p  = 0.028) and increased fibrinogen (FIB) levels ( p  < 0.001), alongside a significant decrease in both diffusing capacity for carbon monoxide (DLCO)% pred ( p  = 0.001) and DLCO/VA% pred ( p  = 0.021) after neoadjuvant therapy compared to pre-indicators. Receiver operating characteristic curve (ROC) analysis showed that the area under the ROC curve of three assessed variables (FIB levels, BMI, DLCO) reached 0.806 in predicting CIP occurrence at an early stage. Conclusions This cohort demonstrated that elevated BMI, increased FIB levels, and decreased pulmonary diffusion function after neoadjuvant therapy are risk factors of CIP occurrence. Early assessment and continuous monitoring of these indicators are imperative for the predictive identification of CIP, enhancing patient management and outcomes.

This study aimed to clarify and provide clinical evidence for which computed tomography (CT) assessment method can more appropriately reflect lung lesion burden of the COVID-19 pneumonia. A total of 244 COVID-19 patients were recruited from three local hospitals. All the patients were assigned to mild, common and severe types. Semi-quantitative assessment methods, e.g., lobar-, segmental-based CT scores and opacity-weighted score, and quantitative assessment method, i.e., lesion volume quantification, were applied to quantify the lung lesions. All four assessment methods had high inter-rater agreements. At the group level, the lesion load in severe type patients was consistently observed to be significantly higher than that in common type in the applications of four assessment methods (all the p < 0.001). In discriminating severe from common patients at the individual level, results for lobe-based, segment-based and opacity-weighted assessments had high true positives while the quantitative lesion volume had high true negatives. In conclusion, both semi-quantitative and quantitative methods have excellent repeatability in measuring inflammatory lesions, and can well distinguish between common type and severe type patients. Lobe-based CT score is fast, readily clinically available, and has a high sensitivity in identifying severe type patients. It is suggested to be a prioritized method for assessing the burden of lung lesions in COVID-19 patients.

Plastic energy dissipation is a key factor in the response of inelastic structures subjected to seismic input, and is often regarded as a primary source of structural damage due to the inelastic deformation of structural components. Accurately predicting a structure’s plastic energy dissipation is essential for efficient energy-based design and seismic assessment. While a single-degree-of-freedom (SDOF) system provides a simple and effective method for estimating plastic energy dissipation, few studies have explored the use of nonlinear analysis methods or equivalent SDOF systems for this purpose. Based on the principle-of-force-analogy method, firstly, the formulas of plastic energy dissipation of a multi-degree-of-freedom (MDOF) system and its equivalent SDOF system were established. Secondly, two estimation methods of plastic energy dissipation of MDOF systems were proposed. Finally, numerical simulations were performed on several multi-story and high-rise structures with varying heights and spans to compare the plastic energy dissipation of MDOF systems and the equivalent SDOF systems of different modes. The simulation results demonstrate that the proposed methods and formulas accurately estimate plastic energy dissipation in multi-story and high-rise structures, while also requiring fewer calculations and less storage.

Background No standardized protocol has been suggested in the treatment of postoperative osteomyelitis following fracture fixation. Our team evaluates the clinical efficacy of the modified algorithm for managing postoperative osteomyelitis following fracture fixation with Cierny–Mader type. Methods Ninety-five wounds were reviewed from March 2009 to February 2016 in our hospital. Sixty-one wounds were treated by the modified algorithm as follows: stable hardware + bone not healed Cierny–Mader 1 type = remove hardware, temporary stabilize; stable hardware + bone not healed Cierny–Mader 2 type = retain hardware ; stable hardware + bone not healed Cierny–Mader for type 3 and type 4 = remove hardware, temporary stabilize/Ilizarov technique; unstable hardware + bone not healed = remove hardware, temporary stabilize/Ilizarov technique; and stable hardware + bone healed = remove hardware. Thirty-four wounds were treated by the conventional algorithm. Autodermoplasty, flap transfer, myocutaneous flap, and other methods including antibiotic irrigation and drug delivery system were used in wound repair. Results The patients treated with modified algorithm had a significantly reduced recurrence ( P < 0.01) and increased results of negative bacterial cultures ( P < 0.01); however, a decrease in the number of retained hardware cases was observed ( P < 0.05). For those treated with tissue reconstruction, there was no significance ( P > 0.05) compared with the conventional group. Conclusions The modified algorithm for the postoperative osteomyelitis following fracture fixation according to the stability of the hardware and Cierny–Mader type represents a good clinical efficacy in the management of postoperative osteomyelitis. This procedure is simple and shows promising results; more clinical evidence is needed to confirm the existing findings and optimize the treatment of postoperative osteomyelitis following fracture fixation.

The structural hydrodynamic response of longline aquaculture facilities under the influence of waves and currents is complex. Studying the hydrodynamic characteristics of this aquaculture structure in complex sea environments can contribute to sustainable offshore aquaculture solutions. Thus, we established a numerical model using AquaSim2.18, a proven and effective finite element hydrodynamic software for analyzing the maximum tension in mooring lines and main lines, the displacement of the main lines, and the forces on the lantern nets under waves and currents. The results showed that positioning the system in the direction of incidence of waves and currents minimizes tension in both mooring and main lines, making a downstream arrangement optimal; compared with a single row, the maximum reduction in the tension of the mooring lines is 3.3% and 1.8% for five-row and row-row lines, respectively, and the shadow effects reduced the downstream mooring force. Additionally, line tension increased with wave height and current velocity, whereas wave periods had variable effects due to the period range; the lantern net forces increased with wave height and decreased with wave period. Wave height was also shown to influence the horizontal displacement of main lines. The findings can provide a reference for the hydrodynamic characteristics of different components of the structure.