Multi-omics analysis to reveal the synergistic mechanism underlying the multiple ingredients of Stephania tetrandra extract on rheumatoid arthritis through the PI3K/Akt signaling pathway.

Background: Stephania tetrandra has been used for treating rheumatic diseases for thousands of years in rural areas of China. Several studies have found that tetrandrine and fangchinoline can inactivate the PI3K/Akt signaling pathway by reducing the expression and phosphorylation of AKT. However, the mechanism underlying the therapeutic actions of S. tetrandra on RA is not well known. Methods: In this study, we determined the molecular mechanism of the therapeutic effects of the multiple ingredients of S. tetrandra extract (STE) on collagen-induced arthritic (CIA) rats by integrating pharmacometabolomics, proteomics, and PTMomics. Results: In the multi-omics joint analysis, first, the expression signatures of proteins, PTMs, metabolites, and STE ingredients were profiled in CIA rats PBMCs that underwent STE treatment. Bioinformatics analysis were subsequently probed that STE mainly regulated tryptophan metabolism, inflammatory response, and cell adhesion pathways in CIA rats. The interrelated pathways were further constructed, and the findings revealed that STE attenuated the inflammatory response and proliferation of PBMCs in CIA rats by mediating the key targets of the PI3K/Akt pathway, including Hint1, ACP1, FGR, HSP90@157W + dioxidation, and Prkca@220N + 845.4540 Da. The rheumatic functions of Hint1 and ACP1 were further confirmed by applying a transcriptomic data of RA patients who clinically received abatacept therapy. Furthermore, a cross-ome correlation analysis was performed and major in vivo ingredients of STE, including coclaurine-N-glucuronide, Me,coclaurine-O-glc, N-gluA-schefferine, corydamine, corypamine, tetrandrine, and fangchiniline, were found to act on these targerts to inactivate the PI3K/Akt pathway. Conclusion: These results elucidated the molecular mechanism by which the ingredients of STE mediate the expression of the key targets in the PI3K/Akt pathway, leading to anti-rheumatic functions. The findings of this study provided new insights into the synergistic effect of STE against arthritis in rats.

Perspectives on phase engineering of nanomaterials.

This perspective highlights the representative progress of phase engineering of nanomaterials (PEN) with an emphasis on noble metals and transition metal dichalcogenides, and proposes future directions in this emerging field.

Pancreatic agenesis and altered m6A methylation in the pancreas of PDX1-mutant cynomolgus macaques.

As an essential transcriptional activator, PDX1 plays a crucial role in pancreatic development and ß-cell function. Mutations in the PDX1 gene may lead to type 4 maturity-onset diabetes of the young (MODY4) and neonatal diabetes mellitus. However, the precise mechanisms underlying MODY4 remain elusive due to the paucity of clinical samples and pronounced differences in pancreatic architecture and genomic composition between humans and existing animal models. In this study, three PDX1-mutant cynomolgus macaques were generated using CRISPR/Cas9 technology, all of which succumbed shortly postpartum, exhibiting pancreatic agenesis. Notably, one tri-allelic PDX1-mutant cynomolgus macaque (designated as M4) developed a pancreas, whereas the two mono-allelic PDX1-mutant cynomolgus macaques displayed no anatomical evidence of pancreatic formation. RNA sequencing of the M4 pancreas revealed substantial molecular changes in both endocrine and exocrine functions, indicating developmental delay and PDX1 haploinsufficiency. A marked change in m6A methylation was identified in the M4 pancreas, confirmed through cultured PDX1-mutant islet organoids. Notably, overexpression of the m6A modulator METTL3 restored function in heterozygous PDX1-mutant islet organoids. This study highlights a novel role of m6A methylation modification in the progression of MODY4 and provides valuable molecular insights for preclinical research.

Development of a prognostic nomogram for esophageal squamous cell carcinoma patients received radiotherapy based on clinical risk factors.

Purpose: The goal of the study was to create a nomogram based on clinical risk factors to forecast the rate of locoregional recurrence-free survival (LRFS) in patients with esophageal squamous cell carcinoma (ESCC) who underwent radiotherapy (RT). Methods: In this study, 574 ESCC patients were selected as participants. Following radiotherapy, subjects were divided into training and validation groups at a 7:3 ratio. The nomogram was established in the training group using Cox regression. Performance validation was conducted in the validation group, assessing predictability through the C-index and AUC curve, calibration via the Hosmer-Lemeshow (H-L) test, and evaluating clinical applicability using decision curve analysis (DCA). Results: T stage, N stage, gross tumor volume (GTV) dose, location, maximal wall thickness (MWT) after RT, node size (NS) after RT, Δ computer tomography (CT) value, and chemotherapy were found to be independent risk factors that impacted LRFS by multivariate cox analysis, and the findings could be utilized to create a nomogram and forecast LRFS. the area under the receiver operating characteristic (AUC) curve and C-index show that for training and validation groups, the prediction result of LRFS using nomogram was more accurate than that of TNM. The LRFS in both groups was consistent with the nomogram according to the H-L test. The DCA curve demonstrated that the nomogram had a good prediction effect both in the groups for training and validation. The nomogram was used to assign ESCC patients to three risk levels: low, medium, or high. There were substantial variations in LRFS between risk categories in both the training and validation groups (p<0.001, p=0.003). Conclusions: For ESCC patients who received radiotherapy, the nomogram based on clinical risk factors could reliably predict the LRFS.

Associations between life's essential 8 and femoral neck bone mineral density among adults: A national population-based study.

Osteoporosis represents a significant public health issue, impacting both health outcomes and economic costs. This research investigates how cardiovascular health, as indicated by the LE8 score, correlates with bone mineral density (BMD). Data from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2018 were analyzed in this cross-sectional analysis, including 9018 subjects following the exclusion of individuals lacking BMD or LE8 data. The LE8 score, comprising factors such as diet, physical activity, smoking status, sleep quality, body mass index, lipid profiles, blood glucose, and blood pressure, was used to evaluate cardiovascular health. BMD was determined through dual-energy X-ray absorptiometry (DXA). Relationships between the LE8 scores and BMD at the femoral neck were assessed using linear regression and smooth curve fitting techniques. Enhanced LE8 scores were linked to improved BMD at the femoral neck. Notably, a 10-point increment in the LE8 score was associated with a rise in BMD by 0.04 g/cm² [ß = 0.04, 95% CI: 0.03-0.05]. The data indicate a strong positive association between cardiovascular health, as measured by LE8, and BMD. These results support the development of holistic health strategies that promote cardiovascular health to potentially improve bone density.

Multiomics analysis of canine myocardium after circumferential pulmonary vein ablation: Effect of neuropeptide Y on long-term reinduction of atrial fibrillation.

Catheter ablation (CA) is an essential method for the interventional treatment of atrial fibrillation (AF), and it is very important to reduce long-term recurrence after CA. The mechanism of recurrence after CA is still unclear. We established a long-term model of beagle canines after circumferential pulmonary vein ablation (CPVA). The transcriptome and proteome were obtained using high-throughput sequencing and TMT-tagged LC-MS/LC analysis, respectively. Differentially expressed genes and proteins were screened and enriched, and the effect of fibrosis was found and verified in tissues. A downregulated protein, neuropeptide Y (NPY), was selected for validation and the results suggest that NPY may play a role in the long-term reinduction of AF after CPVA. Then, the molecular mechanism of NPY was further investigated. The results showed that the atrial effective refractory period (AERP) was shortened and fibrosis was increased after CPVA. Atrial myocyte apoptosis was alleviated by NPY intervention, and Akt activation was inhibited in cardiac fibroblasts. These results suggest that long-term suppression of NPY after CPVA may lead to induction of AF through promoting cardiomyocyte apoptosis and activating the Akt pathway in cardiac fibroblasts, which may make AF more likely to reinduce.

Long-Range π-π Stacking Brings High Electron Delocalization for Enhanced Photocatalytic Activity in Hydrogen-Bonded Organic Framework.

Unlike many studies that regulate transport and separation behaviour of photogenerated charge carriers through controlling the chemical composite, our work demonstrates this goal can be achieved through simply tuning the molecular π-π packing from short-range to long-range within hydrogen-bonded organic frameworks (HOFs) without altering the building blocks or network topology. Further investigations reveal that the long-range π-π stacking significantly promotes electron delocalization and enhances electron density, thereby effectively suppressing electron-hole recombination and augmenting the charge transfer rate. Simultaneously, acting as a porous substrate, it boosts electron density of Pd nanoparticle loaded on its surfaces, resulting in remarkable CO2 photoreduction catalytic activity (CO generation rate: 48.1 µmol/g/h) without the need for hole scavengers. Our study provide insight into regulating the charge carrier behaviours in molecular assemblies based on hydrogen bonds, offering a new clue for efficient photocatalyst design.

Facet-Controlled Synthesis of Unconventional-Phase Metal Alloys for Highly Efficient Hydrogen Oxidation.

Facet control and phase engineering of metal nanomaterials are both important strategies to regulate their physicochemical properties and improve their applications. However, it is still a challenge to tune the exposed facets of metal nanomaterials with unconventional crystal phases, hindering the exploration of the facet effects on their properties and functions. In this work, by using Pd nanoparticles with unconventional hexagonal close-packed (hcp, 2H type) phase, referred to as 2H-Pd, as seeds, a selective epitaxial growth method is developed to tune the predominant growth directions of secondary materials on 2H-Pd, forming Pd@NiRh nanoplates (NPLs) and nanorods (NRs) with 2H phase, referred to as 2H-Pd@2H-NiRh NPLs and NRs, respectively. The 2H-Pd@2H-NiRh NRs expose more (100)h and (101)h facets on the 2H-NiRh shells compared to the 2H-Pd@2H-NiRh NPLs. Impressively, when used as electrocatalysts toward hydrogen oxidation reaction (HOR), the 2H-Pd@2H-NiRh NRs show superior activity compared to the NiRh alloy with conventional face-centered cubic (fcc) phase (fcc-NiRh) and the 2H-Pd@2H-NiRh NPLs, revealing the crucial role of facet control in enhancing the catalytic performance of unconventional-phase metal nanomaterials. Density functional theory (DFT) calculations further unravel that the excellent HOR activity of 2H-Pd@2H-NiRh NRs can be attributed to the more exposed (100)h and (101)h facets on the 2H-NiRh shells, which possess high electron transfer efficiency, optimized H* binding energy, enhanced OH* binding energy, and a low energy barrier for the rate-determining step during the HOR process.

Predicting Intracranial Aneurysm Rupture: A Multifactor Analysis Combining Radscore, Morphology, and PHASES Parameters.

RATIONALE AND OBJECTIVES: We aimed at developing and validating a nomogram and machine learning (ML) models based on radiomics score (Radscore), morphology, and PHASES to predict intracranial aneurysm (IA) rupture. MATERIALS AND METHODS: We collected 440 patients with IAs in our hospital from 2015 to 2023, totaling 475 IAs (214 ruptured and 261 unruptured). A 7:3 random split was utilized to allocate participants into training and testing sets. To optimize the selection of radiomics features extracted from digital subtraction angiography, we employed t-tests and LASSO regression. Subsequently, we built single-factor and multifactor logistic regression (LR) models, alongside a nomogram. Furthermore, we employed four ML algorithms. After a comprehensive evaluation, including area under the curve (AUC), calibration curves, decision curve analysis (DCA), and other metrics, the best model was determined. RESULTS: The AUCs for LR models P (PHASES), M (Morphology), and R (Radscore) in the testing set were 0.859, 0.755, and 0.803, respectively, while those for multifactor models R+M (Radscore and Morphology), R+P (Radscore and PHASES), and R+M+P (Radscore, Morphology, and PHASES) were 0.818, 0.899, and 0.887, respectively. The AUCs of random forest, extreme gradient boosting, gradient boosting machine, and light gradient boosting machine were 0.880, 0.888, 0.891, and 0.892 in testing set, respectively. In the training set, the LR model showed significant differences in AUCs compared with the four ML models (all p < 0.05). However, in the testing set, no statistically significant differences were found between them (all p > 0.05). Both ML models and the nomogram exhibit excellent performance in DCA and calibration curves. CONCLUSION: Nomogram and ML models based on Radscore, morphology, and PHASES show high precision in predicting aneurysm rupture.

RecurIndex-Guided postoperative radiotherapy with or without Avoidance of Irradiation of regional Nodes in 1-3 node-positive breast cancer (RIGAIN): a study protocol for a multicentre, open-label, randomised controlled prospective, phase III trial.

INTRODUCTION: Postoperative radiotherapy in patients with breast cancer with one to three lymph node metastases, particularly within the pT1-2N1M0 cohort with a low clinical risk of local-regional recurrence (LRR), has incited a discourse surrounding personalised treatment strategies. Multigene testing for Recurrence Index (RecurIndex) model capably differentiates patients based on their level of LRR risk. This research aims to validate whether a more aggressive treatment approach can enhance clinical outcomes in N1 patients who possess a clinically low risk of LRR, yet a high RecurIndex-determined risk of LRR. Specifically, this entails postoperative whole breast irradiation combined with regional lymph node irradiation (RNI) following breast-conserving surgery or chest wall irradiation with RNI after mastectomy. METHODS AND ANALYSIS: The RIGAIN (RecurIndex-Guided postoperative radiotherapy with or without Avoidance of Irradiation of regional Nodes in 1-3 node-positive breast cancer) Study is a multicentre, prospective, randomised, open-label, phase III clinical trial that is being conducted in China. In this study, patients with low clinical LRR risk but high RecurIndex-LRR risk are randomly assigned in a 1:1 ratio to the experimental group or the control group. In the experimental group, RNI is performed and the control group omits RNI. Efficacy and safety analyses will be conducted, enrolling a total of 540 patients (270 per group). The primary endpoint is invasive disease-free survival, and secondary endpoints include any first recurrence, LRR-free survival, distant metastasis-free survival, recurrence-free survival, overall survival, disease-free survival, breast cancer-specific mortality and assessment of patient quality of life. The study began in April 2023 and with a follow-up period of 60 months after the last participant completes radiation therapy. ETHICS AND DISSEMINATION: The study was approved by the Ethics Committee of Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University (SYSKY-2022-097-02, V.3.1). It adheres to the Helsinki Declaration and Good Clinical Practice. Research findings will be submitted for publication in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04069884.

Development and External Validation of a Machine Learning-based Fall Prediction Model for Nursing Home Residents: A Prospective Cohort Study.

OBJECTIVES: To develop and externally validate a machine learning-based fall prediction model for ambulatory nursing home residents. The focus is on predicting fall occurrences within 6 months after baseline assessment through a binary classification task, aiming to provide staff with an effective and user-friendly fall-risk assessment tool. DESIGN: Prospective cohort study. SETTING AND PARTICIPANTS: A total of 864 older residents living in 4 nursing homes between May 2022 and March 2023 in China. METHODS: Potential fall-risk predictors were collected through in-person interviews and assessments of anthropometric and physical function. Participants were followed for 6 months, with falls recorded by trained nurses. Seven machine learning algorithms, including Logistic Regression (LR), Gradient Boosting Machine (GBM), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), Neural Networks (NN), and Decision Tree (DT), were used to develop prediction models. Performance was evaluated using the area under the receiver operating characteristic curve (ROC-AUC) and Precision-Recall curve (PR-AUC), with calibration assessed via a calibration curve. Feature importance was visualized using SHapley Additive exPlanations (SHAP). RESULTS: The 6 selected predictors were balance, grip strength, fatigue, fall history, age, and comorbidity. The ROC-AUC for the models ranged from 0.710 to 0.750, PR-AUC from 0.415 to 0.473, sensitivity from 0.704 to 0.914, and specificity from 0.511 to 0.687 in the validation cohort. The LR model was converted into a nomogram. CONCLUSIONS AND IMPLICATIONS: The machine learning-based fall-prediction models effectively identified nursing home residents at high risk of falls. The developed nomogram can be integrated into clinical practice to enhance fall risk assessment protocols, ultimately improving patient safety and care in nursing homes.

Crystal-Phase-Selective Etching of Heterophase Au Nanostructures.

Selective oxidative etching is one of the most effective ways to prepare hollow nanostructures and nanocrystals with specific exposed facets. The mechanism of selective etching in noble metal nanostructures mainly relies on the different reactivity of metal components and the distinct surface energy of multimetallic nanostructures. Recently, phase engineering of nanomaterials (PEN) offers new opportunities for the preparation of unique heterostructures, including heterophase nanostructures. However, the synthesis of hollow multimetallic nanostructures based on crystal-phase-selective etching has been rarely studied. Here, a crystal-phase-selective etching method is reported to selectively etch the unconventional 4H and 2H phases in the heterophase Au nanostructures. Due to the coating of Pt-based alloy and the crystal-phase-selective etching of 4H-Au in 4H/face-centered cubic (fcc) Au nanowires, the well-defined ladder-like Au@PtAg nanoframes are prepared. In addition, the 2H-Au in the fcc-2H-fcc Au nanorods and 2H/fcc Au nanosheets can also be selectively etched using the same method. As a proof-of-concept application, the ladder-like Au@PtAg nanoframes are used for the electrocatalytic hydrogen evolution reaction (HER) in acidic media, showing excellent performance that is comparable to the commercial Pt/C catalyst.

[Effect of CD8+ CD28- T Cells on Acute Graft-Versus-Host Disease after Haploidentical Hematopoietic Stem Cell Transplantation].

OBJECTIVE: To investigate the effect of CD8+ CD28- T cells on acute graft-versus-host disease(aGVHD) after haploidentical hematopoietic stem cell transplantation(haplo-HSCT). METHODS: The relationship between absolute count of CD8+ CD28- T cells and aGVHD in 60 patients with malignant hematological diseases was retrospectively analyzed after haplo-HSCT, and the differences in the incidence rate of chronic graft-versus host disease(cGVHD), infection and prognosis between different CD8+ CD28- T absolute cells count groups were compared. RESULTS: aGVHD occurred in 40 of 60 patients after haplo-HSCT, with an incidence rate of 66.67%. The median occurrence time of aGVHD was 32.5(20-100) days. At 30 days after the transplantation, the absolute count of CD8+ CD28- T cells of aGVHD group was significantly lower than that of non-aGVHD group (P =0.03). Thus the absolute count of CD8+ CD28- T cells at 30 days after transplantation can be used to predict the occurrence of aGVHD to some extent. At 30 days after transplantation, the incidence rate of aGVHD in the low cell count group (CD8+ CD28- T cells absolute count < 0.06/µl) was significantly higher than that in the high cell count group (CD8+ CD28- T cells absolute count ≥0.06/µl,P =0.011). Multivariate Cox regression analysis further confirmed that the absolute count of CD8+ CD28-T cells at 30 days after transplantation was an independent risk factor for aGVHD, and the risk of aGVHD in the low cell count group was 2.222 times higher than that in the high cell count group (P =0.015). The incidence of cGVHD, fungal infection, EBV infection and CMV infection were not significantly different between the two groups with different CD8+ CD28- T cells absolute count. The overall survival, non-recurrent mortality and relapse rates were not significantly different between different CD8+ CD28- T cells absolute count groups. CONCLUSION: Patients with delayed CD8+ CD28- T cells reconstitution after haplo-HSCT are more likely to develop aGVHD, and the absolute count of CD8+ CD28- T cells can be used to predict the incidence of aGVHD to some extent. The absolute count of CD8+ CD28- T cells after haplo-HSCT was not associated with cGVHD, fungal infection, EBV infection, and CMV infection, and was also not significantly associated with the prognosis after transplantation.

Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients.

OBJECTIVE: To investigate the feasibility and accuracy of predicting locoregional recurrence (LR) in elderly patients with esophageal squamous cell cancer (ESCC) who underwent radical radiotherapy using a pairwise machine learning algorithm. METHODS: The 130 datasets enrolled were randomly divided into a training set and a testing set in a 7:3 ratio. Clinical factors were included and radiomics features were extracted from pretreatment CT scans using pyradiomics-based software, and a pairwise naive Bayes (NB) model was developed. The performance of the model was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). To facilitate practical application, we attempted to construct an automated esophageal cancer diagnosis system based on trained models. RESULTS: To the follow-up date, 64 patients (49.23%) had experienced LR. Ten radiomics features and two clinical factors were selected for modeling. The model demonstrated good prediction performance, with area under the ROC curve of 0.903 (0.829-0.958) for the training cohort and 0.944 (0.849-1.000) for the testing cohort. The corresponding accuracies were 0.852 and 0.914, respectively. Calibration curves showed good agreement, and DCA curve confirmed the clinical validity of the model. The model accurately predicted LR in elderly patients, with a positive predictive value of 85.71% for the testing cohort. CONCLUSIONS: The pairwise NB model, based on pre-treatment enhanced chest CT-based radiomics and clinical factors, can accurately predict LR in elderly patients with ESCC. The esophageal cancer automated diagnostic system embedded with the pairwise NB model holds significant potential for application in clinical practice.

Ilizarov technique for treating elbow stiffness caused by myositis ossificans: A case report.

BACKGROUND: Myositis ossificans (MO) is a rare disease involving the formation of bone outside the musculoskeletal system. While surgical intervention is the main treatment approach, preventing recurrence and standardized rehabilitation are also crucial. Here, we present a surgical strategy to prevent the recurrence of MO. CASE SUMMARY: A 28-year-old female patient was admitted for the first time for a comminuted fracture of the left olecranon. However, incorrect postoperative rehabilitation resulted in the development of elbow joint stiffness with ectopic ossification, causing a loss of normal range of motion. The patient was diagnosed with MO based on physical examination, X-ray findings, and clinical presentation. We devised a surgical strategy to remove MO, followed by fixation with an Ilizarov frame, and implemented a scientifically reasonable rehabilitation plan. The surgery lasted for 3 h with an estimated blood loss of 45 mL. A drainage tube was placed after surgery, and fluid was aspirated through ultrasound-guided puncture. The patient experienced a significant reduction in joint stiffness after surgery. In the final follow-up at 9 mouths, there was evident improvement in the range of motion of the elbow joint, and no other symptoms were reported. CONCLUSION: The Ilizarov frame is an advantageous surgical technique for facilitating rehabilitation after MO removal. It offers benefits such as passive recovery, individualized treatment, and prompt recovery.

Prevalence of physical inactivity and its determinants among older adults living in nursing homes: A cross-sectional study based on COM-B model.

AIMS: To investigate the prevalence of physical inactivity in older adults living in nursing homes and explore the determinants of physical inactivity by using the Capability, Opportunity, Motivation-Behaviour model. DESIGN: A multisite, cross-sectional study was performed by convenience sampling and questionnaire survey. METHODS: A total of 390 nursing home residents were recruited from three nursing homes in Southern China from May 2022 to April 2023. The participants completed a self-designed general information questionnaire, Physical Activity Scale for the Elderly, Self-Efficacy for Exercise Scale, Exercise Benefits Scale, Patient Health Questionnaire-9 and the Short Physical Performance Battery test. Descriptive statistics, univariate analysis, Spearman correlation analysis, and ordinal logistic regression were applied for data analysis. RESULTS: The prevalence of physical inactivity among the nursing home residents reached 88.46%. Ordinal logistic regression results showed that exercise self-efficacy, perceived exercise benefits, physical function, availability of physical activity instruction, having depression, number of chronic diseases and living with spouse were the main influencing determinants of physical inactivity and explained 63.7% of the variance. CONCLUSIONS: Physical inactivity was considerable in nursing home residents in China and influenced by complex factors. Tailored measures should be designed and implemented based on these factors to enhance physical activity while considering the uniqueness of Chinese culture. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Healthcare professionals should enhance physical activity of residents by increasing benefits understanding, boosting self-efficacy, improving physical function, alleviating depression and integrating personalized physical activity guidance into routine care services. And more attention should be paid to the residents who had more chronic diseases or did not live with spouse. IMPACT: Physical inactivity is a significant problem in nursing home residents. Understanding physical inactivity and its determinants enables the development of tailored interventions to enhance their physical activity level. REPORTING METHOD: This study was reported conforming to the STROBE statement. PATIENTS OR PUBLIC CONTRIBUTION: Nursing home residents who met the inclusion criteria were recruited.

Lethal pulmonary thromboembolism in mice induced by intravenous human umbilical cord mesenchymal stem cell-derived large extracellular vesicles in a dose- and tissue factor-dependent manner.

Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have obvious advantages over MSC therapy. But the strong procoagulant properties of MSC-EVs pose a potential risk of thromboembolism, an issue that remains insufficiently explored. In this study, we systematically investigated the procoagulant activity of large EVs derived from human umbilical cord MSCs (UC-EVs) both in vitro and in vivo. UC-EVs were isolated from cell culture supernatants. Mice were injected with UC-EVs (0.125, 0.25, 0.5, 1, 2, 4 µg/g body weight) in 100 µL PBS via the tail vein. Behavior and mortality were monitored for 30 min after injection. We showed that these UC-EVs activated coagulation in a dose- and tissue factor-dependent manner. UC-EVs-induced coagulation in vitro could be inhibited by addition of tissue factor pathway inhibitor. Notably, intravenous administration of high doses of the UC-EVs (1 µg/g body weight or higher) led to rapid mortality due to multiple thrombus formations in lung tissue, platelets, and fibrinogen depletion, and prolonged prothrombin and activated partial thromboplastin times. Importantly, we demonstrated that pulmonary thromboembolism induced by the UC-EVs could be prevented by either reducing the infusion rate or by pre-injection of heparin, a known anticoagulant. In conclusion, this study elucidates the procoagulant characteristics and mechanisms of large UC-EVs, details the associated coagulation risk during intravenous delivery, sets a safe upper limit for intravenous dose, and offers effective strategies to prevent such mortal risks when high doses of large UC-EVs are needed for optimal therapeutic effects, with implications for the development and application of large UC-EV-based as well as other MSC-EV-based therapies.

A mathematical model for the role of dopamine-D2 self-regulation in the production of ultradian rhythms.

Many self-motivated and goal-directed behaviours display highly flexible, approximately 4 hour ultradian (shorter than a day) oscillations. Despite lacking direct correspondence to physical cycles in the environment, these ultradian rhythms may be involved in optimizing functional interactions with the environment and reflect intrinsic neural dynamics. Current evidence supports a role of mesostriatal dopamine (DA) in the expression and propagation of ultradian rhythmicity, however, the biochemical processes underpinning these oscillations remain to be identified. Here, we use a mathematical model to investigate D2 autoreceptor-dependent DA self-regulation as the source of ultradian behavioural rhythms. DA concentration at the midbrain-striatal synapses is governed through a dual-negative feedback-loop structure, which naturally gives rise to rhythmicity. This model shows the propensity of striatal DA to produce an ultradian oscillation characterized by a flexible period that is highly sensitive to parameter variations. Circadian (approximately 24 hour) regulation consolidates the ultradian oscillations and alters their response to the phase-dependent, rapid-resetting effect of a transient excitatory stimulus. Within a circadian framework, the ultradian rhythm orchestrates behavioural activity and enhances responsiveness to an external stimulus. This suggests a role for the circadian-ultradian timekeeping hierarchy in governing organized behaviour and shaping daily experience through coordinating the motivation to engage in recurring, albeit not highly predictable events, such as social interactions.

Progress in the treatment of Osteoarthritis with avocado-soybean unsaponifiable.

Osteoarthritis (OA) is one of the leading causes of joint dysfunction and disability in the elderly, posing serious social problems and a huge socio-economic burden. Existing pharmacological treatments have significant drawbacks, and searching for an effective pharmacological intervention is an urgent priority. Recent studies have demonstrated the chondroprotective, anabolic, and anti-catabolic properties of avocado-soybean unsaponifiable (ASU), a natural plant extract made from avocado and soybean oils, consisting of the remainder of the saponified portion of the product that cannot be made into soap. The main components of ASU are phytosterols, beta-sitosterol, canola stanols, and soya stanols, which are rapidly incorporated into cells. Studies have confirmed the anti-inflammatory, antioxidant, and analgesic properties of phytosterols. ASU slows down the progression of OA primarily by inhibiting pathways involved in the development of OA disease. ASU prevents cartilage degradation by inhibiting the release and activity of matrix metalloproteinases and by increasing the tissue inhibition of these catabolic enzymes; ASU is also involved in the inhibition of the activation of nuclear factor κB (NF-κB) which is a transcriptional inhibitor that regulates the inflammatory response of chondrocytes. NF-κB is a transcription factor that regulates the inflammatory response of chondrocytes, and inhibition of the transfer of the transcription factor NF-κB from the cytoplasm to the nucleus regulates the transcription of many pro-inflammatory factors. By appealing to the mechanism of action and thus achieving anti-inflammatory, anti-catabolic, and pro-synthetic effects on cartilage tissues, AUS is clinically responsive to the reduction of acute pain and OA symptom progression. This paper aims to summarize the studies on the use of avocado-soybean unsaponifiable in the pharmacological treatment of osteoarticular.