BACKGROUND:Magnetic nanomaterials have biological activities such as promoting osteogenic differentiation of stem cells and inhibiting osteoclast formation,and can effectively promote the healing of injured bone tissue under the synergistic effect of magnetic fields.They have a very broad application prospect in bone injury repair. OBJECTIVE:To review the mechanism of magnetic nanomaterials and magnetic fields promoting bone repair,as well as their research progress in the field of bone injury repair. METHODS:Relevant literature search was conducted in PubMed and Web of Science databases with the search terms"magnetic nanomaterials,magnetic field,bone repair,bone tissue engineering,stem cell,osteoblast,osteoclast."The time limit of literature search was from 2003 to 2023,which was screened and analyzed.Some classic articles were manually retrieved,and 98 articles were finally included for analysis. RESULTS AND CONCLUSION:(1)Magnetic nanomaterials have biological effects such as promoting osteoblast differentiation,inhibiting osteoclast formation and regulating the immune microenvironment.In addition,magnetic nanomaterials can regulate the physicochemical properties of tissue engineering scaffolds,such as mechanical properties and surface morphology,and endowed with magnetic properties,which is conducive to the regulation of the adhesion,proliferation and osteogenic differentiation of stem cells.(2)The magnetic field has the ability to regulate multiple cell signaling pathways to promote osteoblast differentiation,inhibit osteoclast formation,stimulate angiogenesis and other biological effects,thus accelerating the healing of damaged bone tissue.(3)The joint application of magnetic nanomaterials and magnetic field accelerates the repair of bone damage by activating mechanotransduction,increasing the content of intracellular magnetic nanoparticles,and enhancing the effect of micro-magnetic field,which provides a new idea for the research of bone tissue engineering.(4)Magnetic field has demonstrated definite efficacy in the treatment of clinical fractures,osteoporosis,and osteoarthritis diseases,which is beneficial for bone tissue growth,reducing bone loss,alleviating pain,and improving the quality of life of patients.(5)Magnetic nanomaterials and magnetic fields have great potential for application in bone damage repair and regeneration,but the interaction mechanism between magnetic nanomaterials,magnetic fields,and cells has not been fully elucidated.Moreover,the key parameters of magnetic fields that regulate intracellular molecular events,including the type,intensity,frequency,duration,and mode of the magnetic field,as well as the precise biological effects of a specific magnetic field on osteoblasts and the underlying mechanisms,have yet to be defined.(6)Further attention needs to be paid to the effects on osteoclasts,nerves,blood vessels,and immune cells in the microenvironment of damaged tissues.Finally,the safety of magnetic materials for human use is yet to be systematically studied in terms of their distribution,metabolism,and acute and chronic toxicities.

OBJECTIVE: To evaluate the protective effects of gentiopicroside (GPS) against reactive oxygen species (ROS)-induced NOD-like receptor family, pyrin domain containing 3 (NLRP3) inflammasome activation in endothelial cells, aiming to reduce atherosclerosis. METHODS: Eight-week-old male ApoE-deficient mice were randomly divided into 2 groups (n=10 per group): the vehicle group and the GPS treatment group. Both groups were fed a high-fat diet for 16 weeks. GPS (40 mg/kg per day) was administered by oral gavage to the GPS group, while the vehicle group received an equivalent volume of the vehicle solution. At the end of the treatment, blood and aortic tissues were collected for assessments of atherosclerosis, lipid profiles, oxidative stress, and molecular expressions related to NLRP3 inflammasome activation, ROS production, and apoptosis. Additionally, in vitro experiments on human aortic endothelial cells treated with oxidized low-density lipoprotein (ox-LDL) were conducted to evaluate the effects of GPS on NLRP3 inflammasome activation, pyroptosis, apoptosis, and ROS production, specifically examining the role of the sirtuin 1 (SIRT1)/nuclear factor erythroid 2-related factor 2 (Nrf2) pathway. SIRT1 and Nrf2 inhibitors were used to confirm the pathway's role. RESULTS: GPS treatment significantly reduced atherosclerotic lesions in the en face aorta (P<0.01), as well as in the thoracic and abdominal aortic regions, and markedly decreased sinus lesions within the aortic root (P<0.05 or P<0.01). Additionally, GPS reduced oxidative stress markers and proinflammatory cytokines, including interleukin (IL)-1 β and IL-18, in lesion areas (P<0.05, P<0.01). In vitro, GPS inhibited ox-LDL-induced NLRP3 activation, as evidenced by reduced NLRP3 (P<0.01), apoptosis-associated speck-like protein containing a CARD, cleaved-caspase-1, and cleaved-gasdermin D expressions (all P<0.01). GPS also decreased ROS production, apoptosis, and pyroptosis, with the beneficial effects being significantly reversed by SIRT1 or Nrf2 inhibitors. CONCLUSION GPS exerts an antiatherogenic effect by inhibiting ROS-dependent NLRP3 inflammasome activation via the SIRT1/Nrf2 pathway.
NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Reactive Oxygen Species/metabolism* ; Iridoid Glucosides/therapeutic use* ; NF-E2-Related Factor 2/metabolism* ; Animals ; Atherosclerosis/metabolism* ; Inflammasomes/drug effects* ; Male ; Sirtuin 1/metabolism* ; Signal Transduction/drug effects* ; Humans ; Endothelial Cells/pathology* ; Mice ; Oxidative Stress/drug effects* ; Apoptosis/drug effects* ; Lipoproteins, LDL ; Mice, Inbred C57BL

OBJECTIVES: Managing patients with refractory head and neck cancer pain is one of the more challenging issues in clinical practice, and traditional intrathecal drug delivery also fails to provide adequate analgesia. There are currently no comprehensive and effective treatment methods. This study aims to observe the efficacy and safety of treating intractable head and neck cancer pain with morphine pump via lumbar approach to the prepontine cistern. METHODS: A total of 18 patients with intractable head and neck cancer pain treated with prepontine cistern morphine pumps were selected from the Department of Pain Management, Second Xiangya Hospital, Central South University between September 2019 and July 2023. Statistical analysis was performed on patients' preoperative and postoperative (1 week, 1 month, and 2 months after surgery), Numerical Rating Scale (NRS) scores, Self-Rating Depression Scale (SDS) scores, daily oral morphine consumption, the number of daily breakthrough pain episodes, and postoperative daily intrathecal morphine dosage. RESULTS: The NRS scores, SDS scores, daily oral morphine consumption, and the number of daily breakthrough pain episodes of patients at each time point after surgery were significantly lower than before surgery (all P<0.05). With the gradual increase in the dosage of intrathecal morphine, the daily oral morphine consumption of patients at each postoperative time point was significantly reduced compared to preoperative levels (all P<0.05). The complications related to the operation were mild, including nausea in 5 cases (31.3%), headache in 2 cases (12.5%); hypotension, urine retention, hypersomnia and constipation in 1 case (6.3% each), and no serious adverse events occurred. All improved and were discharged after symptomatic treatment. CONCLUSIONS The implantation of prepontine cistern morphine pump effectively controls intractable head and neck cancer pain, demonstrating characteristics of minimal invasiveness, mild side effects, and low medication dosage under the premise of standardized procedures.
Humans ; Morphine/administration & dosage* ; Male ; Female ; Middle Aged ; Head and Neck Neoplasms/surgery* ; Analgesics, Opioid/administration & dosage* ; Cancer Pain/drug therapy* ; Pain, Intractable/etiology* ; Aged ; Adult ; Infusion Pumps, Implantable ; Pain Management/methods*

Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

OBJECTIVES: To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application. Methods and. RESULTS: Recommendations were formulated based on literature review and expert group discussion, and consensus was reached following expert consultation. The consensus recommendations are comprehensive, covering the entire treatment procedures from preoperative assessment and preparation, surgical operation process, postoperative management and traditional Chinese medicine treatment to individualized treatment planning. The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain, reduced the use of opioid drugs, and significantly improved the quality of life and enhanced immune function of the patients. Postoperative follow-up suggested good treatment tolerance among the patients without serious complications. CONCLUSIONS The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy. The combined treatment has a high clinical value with a good safety profile for management of cancer pain.
Humans ; Medicine, Chinese Traditional ; Cancer Pain/therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Drug Delivery Systems ; Pain Management/methods* ; China

Periodontal bone defects, primarily caused by periodontitis, are highly prevalent in clinical settings and manifest as bone fenestration, dehiscence, or attachment loss, presenting a significant challenge to oral health. In regenerative medicine, harnessing developmental principles for tissue repair offers promising therapeutic potential. Of particular interest is the condensation of progenitor cells, an essential event in organogenesis that has inspired clinically effective cell aggregation approaches in dental regeneration. However, the precise cellular coordination mechanisms during condensation and regeneration remain elusive. Here, taking the tooth as a model organ, we employed single-cell RNA sequencing to dissect the cellular composition and heterogeneity of human dental follicle and dental papilla, revealing a distinct Platelet-derived growth factor receptor alpha (PDGFRA) mesenchymal stem/stromal cell (MSC) population with remarkable odontogenic potential. Interestingly, a reciprocal paracrine interaction between PDGFRA⁺ dental follicle stem cells (DFSCs) and CD31⁺ Endomucin⁺ endothelial cells (ECs) was mediated by Vascular endothelial growth factor A (VEGFA) and Platelet-derived growth factor subunit BB (PDGFBB). This crosstalk not only maintains the functionality of PDGFRA⁺ DFSCs but also drives specialized angiogenesis. In vivo periodontal bone regeneration experiments further reveal that communication between PDGFRA⁺ DFSC aggregates and recipient ECs is essential for effective angiogenic-osteogenic coupling and rapid tissue repair. Collectively, our results unravel the importance of MSC-EC crosstalk mediated by the VEGFA and PDGFBB-PDGFRA reciprocal signaling in orchestrating angiogenesis and osteogenesis. These findings not only establish a framework for deciphering and promoting periodontal bone regeneration in potential clinical applications but also offer insights for future therapeutic strategies in dental or broader regenerative medicine.
Receptor, Platelet-Derived Growth Factor alpha/metabolism* ; Humans ; Neovascularization, Physiologic/physiology* ; Dental Sac/cytology* ; Single-Cell Analysis ; Transcriptome ; Mesenchymal Stem Cells/metabolism* ; Bone Regeneration ; Animals ; Dental Papilla/cytology* ; Periodontium/physiology* ; Stem Cells/metabolism* ; Regeneration ; Angiogenesis

The level of urinary albumin is a critical indicator for the early diagnosis and management of chronic kidney disease (CKD). However, existing methods for detecting albumin are not conducive to point-of-care testing due to the complexity of reagent addition and incubation processes. This study presents a smartphone-integrated handheld automated biochemical analyzer (sHABA) designed for point-of-care testing of urinary albumin. The sHABA features a pre-loaded, disposable reagent cassette with reagents for the albumin assay arranged in the order of their addition within a hose. The smartphone-integrated analyzer can drive the reagents following a preset program, to enable automatic sequential addition. The sHABA has a detection limit for albumin of 5.9 mg/L and a linear detection range from 7 to 450 mg/L. The consistency of albumin level detection in 931 urine samples using sHABA with clinical tests indicates good sensitivity (95.78%) and specificity (90.16%). This research advances the field by providing an automated detection method for albumin in a portable device, allowing even untrained individuals to monitor CKD in real time at the patient's bedside. In the context of promoting tiered diagnosis and treatment, the sHABA has the potential to become an essential tool for the early diagnosis and comprehensive management of CKD and other chronic conditions.

Identifying drug-drug interactions (DDIs) is essential to prevent adverse effects from polypharmacy. Although deep learning has advanced DDI identification, the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits. Here, we developed a Multi-Dimensional Feature Fusion model named MDFF, which integrates one-dimensional simplified molecular input line entry system sequence features, two-dimensional molecular graph features, and three-dimensional geometric features to enhance drug representations for predicting DDIs. MDFF was trained and validated on two DDI datasets, evaluated across three distinct scenarios, and compared with advanced DDI prediction models using accuracy, precision, recall, area under the curve, and F1 score metrics. MDFF achieved state-of-the-art performance across all metrics. Ablation experiments showed that integrating multi-dimensional drug features yielded the best results. More importantly, we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs. Among 12 real-world adverse drug reaction reports, the predictions of 9 reports were supported by relevant evidence. Additionally, MDFF demonstrated the ability to explain adverse DDI mechanisms, providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.

OBJECTIVE: To investigate the feasibility and prognostic implications of assessing volume status during early fluid resuscitation in septic patients based on estimated plasma volume status (ePVS). METHODS: A prospective study was conducted. Patients with sepsis admitted to intensive care unit (ICU) of the First Affiliated Hospital of Kunming Medical University from March to December in 2023 were enrolled. The general information and laboratory indicators at ICU admission were recorded, and ePVS, sequential organ failure assessment (SOFA) score, acute physiology and chronic health status evaluation II (APACHE II) score were calculated. The vital signs, arterial blood gas analysis and volume status related indicators before liquid resuscitation (T0h) and 3 hours (T3h) and 6 hours (T6h) of fluid resuscitation were recorded. The diameter and variability of the inferior vena cava (IVC) were measured by ultrasound, and ePVS, percentage change value of estimated plasma volume status (ΔePVS%), difference in central venous-to-arterial partial pressure of carbon dioxide (Pcv-aCO₂), and lactate clearance rate (LCR) were calculated. Patients were divided into sepsis group and septic shock group based on the diagnosis at ICU admission, and septic patients were subdivided into survival group and death group based on their 28-day survival status. The differences in clinical data between the groups were compared. The correlation between ePVS or ΔePVS% and volume status related indicators during early liquid resuscitation was analyzed by Spearman rank sum correlation test. The predictive value of each variable for 28-day survival in patients with sepsis was analyzed by receiver operator characteristic curve (ROC curve), and 28-day death risk factors were analyzed by Logistic regression method. RESULTS: Fifty-four septic patients were enrolled in the final analysis, including 17 with sepsis and 37 with septic shock; 34 survived at 28 days and 20 died, with a 28-day survival rate of 63.0%. Compared with the sepsis group, the septic shock group had a lower venous ePVS at ICU admission [dL/g: 4.96 (3.67, 7.15) vs. 7.55 (4.36, 10.07), P < 0.05]. Compared with the death group, the survival group had higher T6h arterial and venous ΔePVS%, and albumin [Alb; T6h arterial ΔePVS% (%): 11.57% (-1.82%, 31.35%) vs. 0.48% (-5.67%, 6.02%), T6h venous ΔePVS%: 9.62% (3.59%, 25.75%) vs. 1.52% (-9.65%, 7.72%), Alb (g/L): 27.57±4.15 vs. 23.77±6.97, all P < 0.05], lower SOFA score, APACHE II score, AST, T0h Lac, and T3h and T6h norepinephrine dosage [SOFA score: 9.00 (8.00, 10.00) vs. 11.50 (9.25, 14.50), APACHE II score: 18.00 (14.75, 21.25) vs. 25.50 (21.00, 30.00), AST (U/L): 34.09 (23.20, 56.64) vs. 79.24 (25.34, 196.59), T0h Lac (mmol/L): 1.75 (1.40, 2.93) vs. 3.25 (2.33, 5.30), norepinephrine dosage (mg): 0.98 (< 0.01, 3.10) vs. 4.60 (1.05, 8.55) at T3h, 1.82 (0.38, 5.30) vs. 8.20 (2.80, 17.73) at T6h, all P < 0.05]. While there were no significantly differences in other basic data and ePVS at all of the time points before and after resuscitation between the two groups. Correlation analysis showed that T6h venous ePVS was significantly positively correlated with T6h IVC variability in septic patients (r = 0.360, P < 0.05), T0h arterial ePVS was significantly negatively correlated with T3h and T6h liquid intake volume (r₁ = -0.367, r₂ = -0.280, both P < 0.05), and venous ePVS at ICU admission was significantly positively correlated with NT-proBNP at ICU admission (r = 0.409, P < 0.05). T6h venous ΔePVS% was significantly positively correlated with T3h liquid intake volume and T6h LCR (r₁ = 0.286, r₂ = 0.286, both P < 0.05), and significantly negatively correlated with T6h urine volume and T6h change value of Pcv-aCO₂ (ΔPcv-aCO₂; r₁ = -0.321, r₂ = -0.371, both P < 0.05). ROC curve analysis showed that the area under the ROC curve (AUC) of T6h venous ΔePVS% for predicting 28-day survival in septic patients was 0.726 [95% confidence interval (95%CI) was 0.578-0.875, P = 0.006], with a sensitivity of 82.4%, a specificity of 60.0%, and an optimal cut-off value of 3.09%. Binary multifactorial Logistic regression analysis showed that an increase in T6h venous ΔePVS% was a protective factor for 28-day death in patients with sepsis on early fluid resuscitation [odds ratio (OR) = 0.900, 95%CI was 0.834-0.972, P = 0.007]. CONCLUSIONS ePVS may have potential for assessing the volume status of septic patients during early fluid resuscitation. The ΔePVS% during early fluid resuscitation may help to identify septic patients with a poor prognosis.
Humans ; Prognosis ; Fluid Therapy ; Sepsis/physiopathology* ; Prospective Studies ; Plasma Volume ; Intensive Care Units ; Resuscitation ; Male ; Female ; Middle Aged ; Shock, Septic/therapy*

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms