Oxysophocarpine attenuates inflammatory osteolysis by modulating the NF-κb pathway and the reactive oxygen species-related Nrf2 signaling pathway.

BACKGROUND AND AIM: Inflammatory diseases often result in bone loss due to persistent inflammation, which activates osteoclasts and increases bone resorption. Oxysophocarpine (OSC), a bioalkaloid extracted from the roots of Sophora japonica and other leguminous plants, has neuroprotective and anti-tumor properties. However, it is still uncertain whether OSC can effectively inhibit the differentiation of osteoclasts and bone resorption. Therefore, this study explored the potential role of OSC in osteoclast formation and inflammatory osteolysis and its underlying mechanisms. EXPERIMENTAL PROCEDURE: This study involved inducing primary mouse bone marrow macrophages (BMMs) into osteoclasts using macrophage colony-stimulating factor (M-CSF) and receptor activator of NF-κB ligand (RANKL) and examined the effects of OSC on osteoclast (OC) differentiation, function, and intracellular reactive oxygen species (ROS) production. The impact of OSC on the expression of osteoclast-specific genes and inflammation-related factors was assessed using real-time quantitative PCR. Additionally, changes in oxidative stress-related factors, NF-κB, and MAPK signaling pathways were examined using western blotting. Finally, this study investigated the influence of OSC on a mouse cranial bone resorption model induced by titanium (Ti) particles in vivo. RESULTS: OSC inhibited OC differentiation and resorption and reduces intracellular ROS levels. Moreover, OSC suppressed IL-1ß, TNF-α, IL-6, and osteoclast-specific gene transcription while increasing Nrf2 and HO-1 protein expression. Furthermore, OSC inhibited the expression and autoregulation of the NFATc1 gene, ultimately leading to a reduction in Ti particle-induced bone resorption in mice. CONCLUSION: OSC could be regarded as an innovative medication for the treatment of osteoclast-associated inflammatory osteolytic diseases.

Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis.

Recent studies have provided promising evidence that neuroimaging data can predict treatment outcomes for patients with major depressive disorder (MDD). As most of these studies had small sample sizes, a meta-analysis is warranted to identify the most robust findings and imaging modalities, and to compare predictive outcomes obtained in magnetic resonance imaging (MRI) and studies using clinical and demographic features. We conducted a literature search from database inception to July 22, 2023, to identify studies using pretreatment clinical or brain MRI features to predict treatment outcomes in patients with MDD. Two meta-analyses were conducted on clinical and MRI studies, respectively. The meta-regression was employed to explore the effects of covariates and compare the predictive performance between clinical and MRI groups, as well as across MRI modalities and intervention subgroups. Meta-analysis of 13 clinical studies yielded an area under the curve (AUC) of 0.73, while in 44 MRI studies, the AUC was 0.89. MRI studies showed a higher sensitivity than clinical studies (0.78 vs. 0.62, Z = 3.42, P = 0.001). In MRI studies, resting-state functional MRI (rsfMRI) exhibited a higher specificity than task-based fMRI (tbfMRI) (0.79 vs. 0.69, Z = -2.86, P = 0.004). No significant differences in predictive performance were found between structural and functional MRI, nor between different interventions. Of note, predictive MRI features for treatment outcomes in studies using antidepressants were predominantly located in the limbic and default mode networks, while studies of electroconvulsive therapy (ECT) were restricted mainly to the limbic network. Our findings suggest a promise for pretreatment brain MRI features to predict MDD treatment outcomes, outperforming clinical features. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. Overlapping but distinct network-level measures predicted antidepressants and ECT outcomes. Future studies are needed to predict outcomes using multiple MRI features, and to clarify whether imaging features predict outcomes generally or differ depending on treatments.

Research on a Train Safety Driving Method Based on Fusion of an Incremental Clustering Algorithm and Lightweight Shared Convolution.

This paper addresses the challenge of detecting unknown or unforeseen obstacles in railway track transportation, proposing an innovative detection strategy that integrates an incremental clustering algorithm with lightweight segmentation techniques. In the detection phase, the paper innovatively employs the incremental clustering algorithm as a core method, combined with dilation and erosion theories, to expand the boundaries of point cloud clusters, merging adjacent point cloud elements into unified clusters. This method effectively identifies and connects spatially adjacent point cloud clusters while efficiently eliminating noise from target object point clouds, thereby achieving more precise recognition of unknown obstacles on the track. Furthermore, the effective integration of this algorithm with lightweight shared convolutional semantic segmentation algorithms enables accurate localization of obstacles. Experimental results using two combined public datasets demonstrate that the obstacle detection average recall rate of the proposed method reaches 90.3%, significantly enhancing system reliability. These findings indicate that the proposed detection strategy effectively improves the accuracy and real-time performance of obstacle recognition, thereby presenting important practical application value for ensuring the safe operation of railway tracks.

Microneedle-mediated drug delivery for neurological diseases.

Neurological disorders, including brain injury, brain tumors, and neurodegenerative diseases, rank as the second leading cause of death worldwide. Exploring effective new treatments for neurological disorders has long been a hot research issue in clinical practice. Recently, microneedles (MNs) have attracted much attention due to their designation as a "painless and non-invasive" novel transdermal delivery method, characterized by their biocompatibility and sustainability. The advantages of MNs open an avenue for potential therapeutic interventions targeting neurological disorders. This review presents a concise overview of progress in the field of MNs, with highlights on the application in the treatment of neurological disorders. Notably, trends in the development of MNs and future challenges are also discussed.

Fine-tuning large language models for chemical text mining.

Extracting knowledge from complex and diverse chemical texts is a pivotal task for both experimental and computational chemists. The task is still considered to be extremely challenging due to the complexity of the chemical language and scientific literature. This study explored the power of fine-tuned large language models (LLMs) on five intricate chemical text mining tasks: compound entity recognition, reaction role labelling, metal-organic framework (MOF) synthesis information extraction, nuclear magnetic resonance spectroscopy (NMR) data extraction, and the conversion of reaction paragraphs to action sequences. The fine-tuned LLMs demonstrated impressive performance, significantly reducing the need for repetitive and extensive prompt engineering experiments. For comparison, we guided ChatGPT (GPT-3.5-turbo) and GPT-4 with prompt engineering and fine-tuned GPT-3.5-turbo as well as other open-source LLMs such as Mistral, Llama3, Llama2, T5, and BART. The results showed that the fine-tuned ChatGPT models excelled in all tasks. They achieved exact accuracy levels ranging from 69% to 95% on these tasks with minimal annotated data. They even outperformed those task-adaptive pre-training and fine-tuning models that were based on a significantly larger amount of in-domain data. Notably, fine-tuned Mistral and Llama3 show competitive abilities. Given their versatility, robustness, and low-code capability, leveraging fine-tuned LLMs as flexible and effective toolkits for automated data acquisition could revolutionize chemical knowledge extraction.

In silico off-target profiling for enhanced drug safety assessment.

Ensuring drug safety in the early stages of drug development is crucial to avoid costly failures in subsequent phases. However, the economic burden associated with detecting drug off-targets and potential side effects through in vitro safety screening and animal testing is substantial. Drug off-target interactions, along with the adverse drug reactions they induce, are significant factors affecting drug safety. To assess the liability of candidate drugs, we developed an artificial intelligence model for the precise prediction of compound off-target interactions, leveraging multi-task graph neural networks. The outcomes of off-target predictions can serve as representations for compounds, enabling the differentiation of drugs under various ATC codes and the classification of compound toxicity. Furthermore, the predicted off-target profiles are employed in adverse drug reaction (ADR) enrichment analysis, facilitating the inference of potential ADRs for a drug. Using the withdrawn drug Pergolide as an example, we elucidate the mechanisms underlying ADRs at the target level, contributing to the exploration of the potential clinical relevance of newly predicted off-target interactions. Overall, our work facilitates the early assessment of compound safety/toxicity based on off-target identification, deduces potential ADRs of drugs, and ultimately promotes the secure development of drugs.

Linked patterns of symptoms and cognitive covariation with functional brain controllability in major depressive disorder.

BACKGROUND: Controllability analysis is an approach developed for evaluating the ability of a brain region to modulate function in other regions, which has been found to be altered in major depressive disorder (MDD). Both depressive symptoms and cognitive impairments are prominent features of MDD, but the case-control differences of controllability between MDD and controls can not fully interpret the contribution of both clinical symptoms and cognition to brain controllability and linked patterns among them in MDD. METHODS: Sparse canonical correlation analysis was used to investigate the associations between resting-state functional brain controllability at the network level and clinical symptoms and cognition in 99 first-episode medication-naïve patients with MDD. FINDINGS: Average controllability was significantly correlated with clinical features. The average controllability of the dorsal attention network (DAN) and visual network had the highest correlations with clinical variables. Among clinical variables, depressed mood, suicidal ideation and behaviour, impaired work and activities, and gastrointestinal symptoms were significantly negatively associated with average controllability, and reduced cognitive flexibility was associated with reduced average controllability. INTERPRETATION: These findings highlight the importance of brain regions in modulating activity across brain networks in MDD, given their associations with symptoms and cognitive impairments observed in our study. Disrupted control of brain reconfiguration of DAN and visual network during their state transitions may represent a core brain mechanism for the behavioural impairments observed in MDD. FUNDING: National Natural Science Foundation of China (82001795 and 82027808), National Key R&D Program (2022YFC2009900), and Sichuan Science and Technology Program (2024NSFSC0653).

Nanosilicate-reinforced GelMA-PEGDA hydrogel promotes angiogenesis for bone regeneration.

Bone tissue engineering has emerged as a pivotal field addressing the critical clinical needs of bone fractures. This study focused on developing multi-composite hydrogels by synergizing biocompatible GelMA macromolecules with synthetic PEGDA and reinforcing them with nanosilicates (SN). The incorporation of SN introduces crucial trace elements such as silicon, magnesium, and lithium, promoting both angiogenesis and osteogenesis. Characterizations revealed that PEGDA significantly reinforced the composite hydrogels' stability, while SN further enhanced the mechanical integrity of the GelMA-PEGDA-SN (GPS) hydrogels. Cell studies designated that GPS improved cell proliferation and migration, angiogenic VEGF/eNOS expression and osteogenic differentiation. In vivo experiments showed that GPS hydrogels effectively enhanced calvarial bone healing, with the GPS-2 formulation (2 % SN) displaying superior bone coverage and increased vascular formation. Assessments of osteogenic formation and the angiogenic marker CD31 validated the comprehensive bone regeneration potential of GPS hydrogels. These findings highlight the significant promise of GPS hydrogels in fostering bone healing with promoted angiogenesis.

3D-printed Personalized Porous Acetabular Component to Reconstruct Extensive Acetabular Bone Defects in Primary Hip Arthroplasty.

OBJECTIVE: Management of extensive acetabular bone defects in total hip arthroplasty (THA) remains challenging. This study aims to investigate the feasibility and preliminary outcomes of 3D-printed personalized porous acetabular components for the reconstruction of acetabular defects in primary THA. METHODS: This retrospective study involved seven patients who received 3D-printed acetabular components in primary THA between July 2018 and March 2021. Preoperatively, acetabular bone defects were evaluated by referencing the Paprosky classification. There were two "Paprosky type IIIA" defects and five "Paprosky type IIIB" defects. The acetabular components were custom-made for each patient to reconstruct the extensive acetabular defects. The hip function was assessed according to the Harris hip score (HHS). Clinical and radiographic outcomes were assessed. RESULTS: The average follow-up period was 40 months, ranging from 26 to 57 months. There were no patients lost to follow-up. The HHS improved from 44 (range: 33-53) before the operation to 88 (range: 79-93) at the final follow-up. Postoperative X-rays showed that the 3D-printed personalized components were properly fitted with the acetabulum. The average center of rotation (COR) discrepancy was 2.3 mm horizontally and 2.1 mm vertically, respectively. Tomosynthesis-Shimadzu metal artifact reduction technology images showed that the implant was in close contact with the host bone. Moreover, no complications were observed during the follow-up period, including loosening, dislocation, or component protrusion. CONCLUSION: The implantation of 3D-printed personalized acetabular components showed accurate reconstruction, stable mechanical support, and favorable function at short-term follow-up. This may be a viable alternative method for reconstructing extensive acetabular defects in THA.

Advanced Pelvic Girdle Reconstruction with three dimensional-printed Custom Hemipelvic Endoprostheses following Pelvic Tumour Resection.

PURPOSE: Resection of pelvic bone tumours and subsequent pelvic girdle reconstruction pose formidable challenges due to the intricate anatomy, weight-bearing demands, and significant defects. 3D-printed implants have improved pelvic girdle reconstruction by enabling precise resections with customized guides, offering tailored solutions for diverse bone defect morphology, and integrating porous surface structures to promote osseointegration. Our study aims to evaluate the long-term efficacy and feasibility of 3D-printed hemipelvic reconstruction following resection of malignant pelvic tumours. METHODS: A retrospective review was conducted on 96 patients with primary pelvic malignancies who underwent pelvic girdle reconstruction using 3D-printed custom hemipelvic endoprostheses between January 2017 and May 2022. Follow-up duration was median 48.1 ± 17.9 months (range, 6 to 76 months). Demographic data, imaging examinations, surgical outcomes, and oncological evaluations were extracted and analyzed. The primary endpoints included oncological outcomes and functional status assessed by the Musculoskeletal Tumor Society (MSTS-93) score. Secondary endpoints comprised surgical duration, intraoperative bleeding, pain control and complications. RESULTS: In 96 patients, 70 patients (72.9%) remained disease-free, 15 (15.6%) had local recurrence, and 11 (11.4%) succumbed to metastatic disease. Postoperatively, function improved with MSTS-93 score increasing from 12.2 ± 2.0 to 23.8 ± 3.8. The mean operating time was 275.1 ± 94.0 min, and the mean intraoperative blood loss was 1896.9 ± 801.1 ml. Pain was well-managed, resulting in substantial improvements in VAS score (5.3 ± 1.8 to 1.4 ± 1.1). Complications occurred in 13 patients (13.5%), including poor wound healing (6.3%), deep prosthesis infection (4.2%), hip dislocation (2.1%), screw fracture (1.0%), and interface loosening (1.0%). Additionally, all patients achieved precise implantation of customized prosthetics according to preoperative plans. T-SMART revealed excellent integration at the prosthesis-bone interface for all patients. CONCLUSION: The use of a 3D-printed custom hemipelvic endoprosthesis, characterized by anatomically designed contours and a porous biomimetic surface structure, offers a potential option for pelvic girdle reconstruction following internal hemipelvectomy in primary pelvic tumor treatment. Initial results demonstrate stable fixation and satisfactory mid-term functional and radiographic outcomes.

Efficacy and safety of anlotinib in patients with desmoid fibromatosis: a retrospective analysis.

Introduction: Desmoid fibromatosis is an aggressive fibroblastic neoplasm with a high propensity for local recurrence. Targeted therapy for Desmoid fibromatosis represents a novel avenue in systemic treatment. Anlotinib, a novel multitargeted angiogenesis inhibitor, represents a novel approach for targeted therapy. Therefore, this study aims to assess the efficacy and safety of anlotinib in patients with Desmoid fibromatosis. Methods: We retrospectively gathered the clinical medical records of Desmoid fibromatosis patients who underwent anlotinib treatment between June 2019 and November 2023 at our center. Anlotinib was initiated at a daily dose of 12 mg and adjusted based on drug-related toxicity. Tumor response was evaluated using the Response Evaluation Criteria in Solid Tumors 1.1 criteria. Progression-free survival served as the primary endpoint and was analyzed utilizing the Kaplan-Meier method. Results: In total, sixty-six consecutive patients were enrolled. No patients achieved a complete response; however, fourteen patients (21.21%) exhibited a partial response, while forty-six patients (70%) experienced disease stability. Progressive disease was observed in 6 patients (9.10%), and the progression-free survival rates at 12 and 36months were 89.71% and 82.81%, respectively. The disease control rate was 90.91%, while the objective response rate was 21.21%. Conclusion: Anlotinib proves effective in managing recurrent and symptomatic patients with Desmoid fibromatosis. However, the toxicity profile of anlotinib presents a higher risk of Hand-Foot Skin Reaction and hypertension. Therefore, given that 41.67% of patients were subjected to dose adjustments associated with the initial dose of 12 mg, implementing dosage reductions may help balance efficacy with side effects.

Is 3D-printed self-stabilizing endoprosthesis reconstruction without supplemental fixation following total sacrectomy a viable approach for sacral tumours?

PURPOSE: The spinopelvic reconstruction poses significant challenges following total sacrectomy in patients with malignant or aggressive benign bone tumours encompassing the entire sacrum. In this study, we aim to assess the functional outcomes and complications of an integrated 3D-printed sacral endoprostheses featuring a self-stabilizing design, eliminating the requirement for supplemental fixation. METHODS: We retrospectively analyzed patients with sacral tumours who underwent total sacrectomy followed by reconstruction with 3D-printed self-stabilizing endoprosthesis. Clinically, we evaluated functional outcomes using the 1993 version of the musculoskeletal tumour society (MSTS-93) score. Perioperative and postoperative complications were also documented. RESULTS: 10 patients met final inclusion criteria. The median age was 49 years (range, 31-64 years). The median follow-up time was 26.5 months (range, 15-47 months). Median postoperative functional MSTS-93 was 22.5 (range, 13-25). The median operation time was 399.5 min (305-576 min), and the median intraoperative blood loss was and 3200 ml (2400-7800 ml). Complications include wound dehiscence in one patient, bowel, bladder, and sexual dysfunction in four patients, cerebrospinal fluid leak in one patient, and tumour recurrence in one patient. There were no mechanical complications related to the endoprosthesis at the last follow-up. CONCLUSION: The utilization of 3D-printed self-stabilizing endoprosthesis proved to be a viable approach, yielding satisfactory short-term outcomes in patients undergoing total sacral reconstruction without supplemental fixation.

Artemisinic acid attenuates osteoclast formation and titanium particle-induced osteolysis via inhibition of RANKL-induced ROS accumulation and MAPK and NF-κB signaling pathways.

Periprosthetic osteolysis (PPO) is the most common cause of joint arthroplasty failure. Its progression involves both biological and mechanical factors. Osteoclastogenesis induced by wear from debris-cell interactions, ultimately leading to excessive bone erosion, is considered the primary cause of PPO; therefore, targeting osteoclasts is a promising treatment approach. Currently available drugs have various side effects and limitations. Artemisinic acid (ArA) is a sesquiterpene isolated from the traditional herb Artemisia annua L. that has various pharmacological effects, such as antimalarial, anti-inflammatory, and antioxidant activities. Therefore, this study was aimed at investigating the effect of ArA on osteoclast formation and bone resorption function in vitro, as well as wear particle-induced osteolysis in vivo, and to explore its molecular mechanism of action. Here, we report that ArA inhibits RANKL-stimulated osteoclast formation and function. Mechanistically, ArA suppresses intracellular reactive oxygen species levels by activating the antioxidant response via nuclear factor erythroid-2-related factor 2 (Nrf2) pathway upregulation. It also inhibits the mitogen-activated kinases (MAPK) and nuclear factor-κB (NF-κB) pathways, as well as the transcription and expression of NFATc1 and c-Fos. In vivo experiments demonstrated that ArA reduces osteoclast formation and alleviates titanium particle-induced calvarial osteolysis. Collectively, our study highlights that ArA, with its osteoprotective and antioxidant effects, is a promising therapeutic agent for preventing and treating PPO and other osteoclast-mediated osteolytic diseases.

3D-Printed custom-made hemipelvic endoprosthetic reconstruction following periacetabular tumor resection: utilizing a novel classification system.

BACKGROUND: Customized 3D-printed pelvic implants with a porous structure have revolutionized periacetabular pelvic defect reconstruction after tumor resection, offering improved osteointegration, long-term stability, and anatomical fit. However, the lack of an established classification system hampers implementation and progress. METHODS: We formulated a novel classification system based on pelvic defect morphology and 3D-printed hemipelvis endoprostheses. It integrates surgical approach, osteotomy guide plate and prosthesis design, postoperative rehabilitation plans, and perioperative processes. RESULTS: Retrospectively analyzing 60 patients (31 males, 29 females), we classified them into Type A (15 patients: Aa = 6, Ab = 9), Type B (27 patients: Ba = 15, Bb = 12), Type C (17 patients). All underwent customized osteotomy guide plate-assisted tumor resection and 3D-printed hemipelvic endoprosthesis reconstruction. Follow-up duration was median 36.5 ± 15.0 months (range, 6 to 74 months). The mean operating time was 430.0 ± 106.7 min, intraoperative blood loss 2018.3 ± 1305.6 ml, transfusion volume 2510.0 ± 1778.1 ml. Complications occurred in 13 patients (21.7%), including poor wound healing (10.0%), deep prosthesis infection (6.7%), hip dislocation (3.3%), screw fracture (1.7%), and interface loosening (1.7%). VAS score improved from 5.5 ± 1.4 to 1.7 ± 1.3, MSTS-93 score from 14.8 ± 2.5 to 23.0 ± 5.6. Implant osseointegration success rate was 98.5% (128/130), with one Type Ba patient experiencing distal prosthesis loosening. CONCLUSION: The West China classification may supplement the Enneking and Dunham classification, enhancing interdisciplinary communication and surgical outcomes. However, further validation and wider adoption are required to confirm clinical effectiveness.

Three-dimensional printed custom-made modular talus prosthesis in patients with talus malignant tumor resection.

BACKGROUND: Talar malignant tumor is extremely rare. Currently, there are several alternative management options for talus malignant tumor including below-knee amputation, tibio-calcaneal arthrodesis, and homogenous bone transplant while their shortcomings limited the clinical application. Three-dimensional (3D) printed total talus prosthesis in talus lesion was reported as a useful method to reconstruct talus, however, most researches are case reports and its clinical effect remains unclear. Therefore, the current study was to explore the application of 3D printed custom-made modular prosthesis in talus malignant tumor. METHODS: We retrospectively analyzed the patients who received the 3D printed custom-made modular prosthesis treatment due to talus malignant tumor in our hospital from February 2016 to December 2021. The patient's clinical data such as oncology outcome, operation time, and volume of blood loss were recorded. The limb function was evaluated with the Musculoskeletal Tumor Society 93 (MSTS-93) score, The American Orthopedic Foot and Ankle Society (AOFAS) score; the ankle joint ranges of motion as well as the leg length discrepancy were evaluated. Plain radiography and Tomosynthesis-Shimadzu Metal Artefact Reduction Technology (T-SMART) were used to evaluate the position of prosthesis and the osseointegration. Postoperative complications were recorded. RESULTS: The average patients' age and the follow-up period were respectively 31.5 ± 13.1 years; and 54.8 months (range 26-72). The medium operation time was 2.4 ± 0.5 h; the intraoperative blood loss was 131.7 ± 121.4 ml. The mean MSTS-93 and AOFAS score was 26.8 and 88.5 respectively. The average plantar flexion, dorsiflexion, varus, and valgus were 32.5, 9.2, 10.8, and 5.8 degree respectively. One patient had delayed postoperative wound healing. There was no leg length discrepancy observed in any patient and good osseointegration was observed on the interface between the bone and talus prosthesis in all subjects. CONCLUSION: The modular structure of the prosthesis developed in this study seems to be convenient for prosthesis implantation and screws distribution. And the combination of solid and porous structure improves the initial stability and promotes bone integration. Therefore, 3D printed custom-made modular talus prosthesis could be an alternative option for talus reconstruction in talus malignant tumor patients.

Transcriptomic and cellular decoding of scaffolds-induced suture mesenchyme regeneration.

Precise orchestration of cell fate determination underlies the success of scaffold-based skeletal regeneration. Despite extensive studies on mineralized parenchymal tissue rebuilding, regenerating and maintaining undifferentiated mesenchyme within calvarial bone remain very challenging with limited advances yet. Current knowledge has evidenced the indispensability of rebuilding suture mesenchymal stem cell niches to avoid severe brain or even systematic damage. But to date, the absence of promising therapeutic biomaterials/scaffolds remains. The reason lies in the shortage of fundamental knowledge and methodological evidence to understand the cellular fate regulations of scaffolds. To address these issues, in this study, we systematically investigated the cellular fate determinations and transcriptomic mechanisms by distinct types of commonly used calvarial scaffolds. Our data elucidated the natural processes without scaffold transplantation and demonstrated how different scaffolds altered in vivo cellular responses. A feasible scaffold, polylactic acid electrospinning membrane (PLA), was next identified to precisely control mesenchymal ingrowth and self-renewal to rebuild non-osteogenic suture-like tissue at the defect center, meanwhile supporting proper osteointegration with defect bony edges. Especially, transcriptome analysis and cellular mechanisms underlying the well-orchestrated cell fate determination of PLA were deciphered. This study for the first time cellularly decoded the fate regulations of scaffolds in suture-bony composite defect healing, offering clinicians potential choices for regenerating such complicated injuries.

Advancements in Photothermal Therapy Using Near-Infrared Light for Bone Tumors.

Bone tumors, particularly osteosarcoma, are prevalent among children and adolescents. This ailment has emerged as the second most frequent cause of cancer-related mortality in adolescents. Conventional treatment methods comprise extensive surgical resection, radiotherapy, and chemotherapy. Consequently, the management of bone tumors and bone regeneration poses significant clinical challenges. Photothermal tumor therapy has attracted considerable attention owing to its minimal invasiveness and high selectivity. However, key challenges have limited its widespread clinical use. Enhancing the tumor specificity of photosensitizers through targeting or localized activation holds potential for better outcomes with fewer adverse effects. Combinations with chemotherapies or immunotherapies also present avenues for improvement. In this review, we provide an overview of the most recent strategies aimed at overcoming the limitations of photothermal therapy (PTT), along with current research directions in the context of bone tumors, including (1) target strategies, (2) photothermal therapy combined with multiple therapies (immunotherapies, chemotherapies, and chemodynamic therapies, magnetic, and photodynamic therapies), and (3) bifunctional scaffolds for photothermal therapy and bone regeneration. We delve into the pros and cons of these combination methods and explore current research focal points. Lastly, we address the challenges and prospects of photothermal combination therapy.

Biomimetic design and clinical application of Ti-6Al-4V lattice hemipelvis prosthesis for pelvic reconstruction.

OBJECTIVE: This study aims to biomimetic design a new 3D-printed lattice hemipelvis prosthesis and evaluate its clinical efficiency for pelvic reconstruction following tumor resection, focusing on feasibility, osseointegration, and patient outcomes. METHODS: From May 2020 to October 2021, twelve patients with pelvic tumors underwent tumor resection and subsequently received 3D-printed lattice hemipelvis prostheses for pelvic reconstruction. The prosthesis was strategically incorporated with lattice structures and solid to optimize mechanical performance and osseointegration. The pore size and porosity were analyzed. Patient outcomes were assessed through a combination of clinical and radiological evaluations. RESULTS: Multiple pore sizes were observed in irregular porous structures, with a wide distribution range (approximately 300-900 µm). The average follow-up of 34.7 months, ranging 26 from to 43 months. One patient with Ewing sarcoma died of pulmonary metastasis 33 months after surgery while others were alive at the last follow-up. Postoperative radiographs showed that the prosthesis's position was consistent with the preoperative planning. T-SMART images showed that the host bone was in close and tight contact with the prosthesis with no gaps at the interface. The average MSTS score was 21 at the last follow-up, ranging from 18 to 24. There was no complication requiring revision surgery or removal of the 3D-printed hemipelvis prosthesis, such as infection, screw breakage, and prosthesis loosening. CONCLUSION: The newly designed 3D-printed lattice hemipelvis prosthesis created multiple pore sizes with a wide distribution range and resulted in good osteointegration and favorable limb function.

Characterization of an exopolysaccharide synthesized by Lacticaseibacillus rhamnosus B6 and its immunomodulatory activity in vitro.

An exopolysaccharide, designated F1, was purified from the fermented milk by Lacticaseibacillus rhamnosus strain B6 (CGMCC No. 13310). F1, with the weight average molecular weight of 1.577 × 106 Da, is consisted of rhamnose, glucose and galactose in a molar ratio of 3.7:1.5: 1. The backbone included 1,3-linked Rha, 1,2,3-linked Rha, 1,2-linked Glc and 1,3-linked Glc residues, with the branching point located at O2 position of 1,2,3-linked Rha residue, and the branch chain composed of terminal linked galactose residue with a pyruvate substituent. F1 could significantly stimulate the phagocytic activity and TNF-α expression in RAW 264.7 macrophages in a dose-dependent manner, and the release of NO at 200 µg/mL as well. F1 at 200 µg/mL could stimulate the expression of the pro-inflammatory cytokine encoding genes including TNF-α and iNOS, but with a negligible upregulating effect on the mRNA expression of IL-10. F1 could up-regulate the expression of NF-κBp65 and skew macrophage polarization towards M1 phenotype. These results suggest F1 elicit an immunomodulatory effect through the NF-κB signaling pathway.

Application of ensemble learning for predicting GABAA receptor agonists.

BACKGROUND: Over the past few decades, agonists binding to the benzodiazepine site of the GABAA receptor have been successfully developed as clinical drugs. Different modulators (agonist, antagonist, and reverse agonist) bound to benzodiazepine sites exhibit different or even opposite pharmacological effects, however, their structures are so similar that it is difficult to distinguish them based solely on molecular skeleton. This study aims to develop classification models for predicting the agonists. METHODS: 306 agonists or non-agonists were collected from literature. Six machine learning algorithms including RF, XGBoost, AdaBoost, GBoost, SVM, and ANN algorithms were employed for model development. Using six descriptors including 1D/2D Descriptors, ECFP4, 2D-Pharmacophore, MACCS, PubChem, and Estate fingerprint to characterize chemical structures. The model interpretability was explored by SHAP method. RESULTS: The best model demonstrated an AUC value of 0.905 and an MCC value of 0.808 for the test set. The PubMac-based model (PubMac-GB) achieved best AUC values of 0.935 for test set. The SHAP analysis results emphasized that MaccsFP62, ECFP_624, ECFP_724, and PubchemFP213 were the crucial molecular features. Applicability domain analysis was also performed to determine reliable prediction boundaries for the model. The PubMac-GB model was applied to virtual screening for potential GABAA agonists and the top 100 compounds were given. CONCLUSION: Overall, our ensemble learning-based model (PubMac-GB) achieved comparable performance and would be helpful in effectively identifying agonists of GABAA receptors.