Discovery of Potent and Selective c-Met Degraders for Hepatocellular Carcinoma Treatment.

Targeting c-Met is a clinical trend for the precise treatment of HCC, but the potential issue of acquired drug resistance cannot be ignored. Targeted protein degradation technology has demonstrated promising prospects in disease treatment and overcoming drug resistance due to its special mechanism of action. In this study, we designed and synthesized two series of novel c-Met degraders and conducted a systematic biological evaluation of the optimal compound H11. H11 exhibited good c-Met degradation activity and anti-HCC activity. Importantly, H11 also demonstrated more potent inhibitory activity against Ba/F3-TPR-MET-D1228N and Ba/F3-TPR-MET-Y1230H cell lines than did tepotinib. In summary, H11 displayed potent anti-HCC activity as a degrader and may overcome resistance to type Ib inhibitors, making it a new therapeutic strategy for HCC with MET alterations.

Costunolide Inhibits Chronic Kidney Disease Development by Attenuating IKKß/NF-κB Pathway.

Background: Chronic kidney disease (CKD) is a significant worldwide health concern that leads to high mortality rates. The bioactive substance costunolide (CTD) has demonstrated several pharmacological effects and holds promise as a CKD treatment. This study aims to investigate the impact of CTD on CKD and delve into its mechanisms of action. Methods: Unilateral ureteral obstruction (UUO) methods and renal fibrosis mice models were created. Various concentrations of CTD were injected into UUO mice models to investigate the therapeutic effects of CTD on renal fibrosis of mice. Then, renal morphology, pathological changes, and the expression of genes related to fibrosis, inflammation and ferroptosis were analysed. RNA sequencing was utilized to identify the main biological processes and pathways involved in renal injury. Finally, both overexpression and inhibition of IKKß were studied to examine their respective effects on fibrosis and inflammation in both in vitro and in vivo models. Results: CTD treatment was found to significantly alleviate fibrosis, inflammation and ferroptosis in UUO-induced renal fibrosis mice models. The results of RNA sequencing suggested that the IKKß acted as key regulatory factor in renal injury and the expression of IKKß was increased in vitro and in vivo renal fibrosis model. Functionally, down-regulated IKKß expression inhibits ferroptosis, inflammatory cytokine production and collagen deposition. Conversely, IKKß overexpression exacerbates progressive renal fibrosis. Mechanistically, CTD alleviated renal fibrosis and inflammation by inhibiting the expression of IKKß and attenuating IKKß/NF-κB pathway. Conclusion: This study demonstrates that CTD could mitigate renal fibrosis, ferroptosis and inflammation in CKD by modulating the IKKß/NF-κB pathway, which indicates targeting IKKß has an enormous potential for treating CKD.

Wavelength-tunable high-fidelity entangled photon sources enabled by dual Stark effects.

The construction of a large-scale quantum internet requires quantum repeaters containing multiple entangled photon sources with identical wavelengths. Semiconductor quantum dots can generate entangled photon pairs deterministically with high fidelity. However, realizing wavelength-matched quantum-dot entangled photon sources faces two difficulties: the non-uniformity of emission wavelength and exciton fine-structure splitting induced fidelity reduction. Typically, these two factors are not independently tunable, making it challenging to achieve simultaneous improvement. In this work, we demonstrate wavelength-tunable entangled photon sources based on droplet-etched GaAs quantum dots through the combined use of AC and quantum-confined Stark effects. The emission wavelength can be tuned by ~1 meV while preserving an entanglement fidelity f exceeding 0.955(1) in the entire tuning range. Based on this hybrid tuning scheme, we finally demonstrate multiple wavelength-matched entangled photon sources with f > 0.919(3), paving the way towards robust and scalable on-demand entangled photon sources for quantum internet and integrated quantum optical circuits.

Clinical and multimodal imaging features of adult-onset neuronal intranuclear inclusion disease.

OBJECTIVES: This study aimed to analyze the clinical and multimodal imaging manifestations of adult-onset neuronal intranuclear inclusion disease (NIID) patients and to investigate NIID-specific neuroimaging biomarkers. METHODS: Forty patients were retrospectively enrolled from the Qilu Hospital of Shandong University. We analyzed the clinical and imaging characteristics of 40 adult-onset NIID patients and investigated the correlation between these characteristics and genetic markers and neuropsychological scores. We further explored NIID-specific alterations using multimodal imaging indices, including diffusion tensor imaging (DTI), magnetic resonance spectroscopy (MRS), and brain age estimation. In addition, we summarized the dynamic evolution pattern of NIID by examining the changes in diffusion weighted imaging (DWI) signals over time. RESULTS: The NIID patients' ages ranged from 31 to 77 years. Cognitive impairment was the most common symptom (30/40, 75.0%), while some patients (18/40, 45.0%) initially presented with episodic symptoms such as headache (10/40, 25.0%). Patients with cognitive impairment symptoms had more cerebral white matter damage (χ2 = 11.475, P = 0.009). The most prevalent imaging manifestation was a high signal on DWI in the corticomedullary junction area, which was observed in 80.0% (32/40) of patients. In addition, the DWI dynamic evolution patterns could be classified into four main patterns. Diffusion tensor imaging (DTI) revealed extensive thinning of cerebral white matter fibers. The estimated brain age surpassed the patient's chronological age, signifying advanced brain aging in NIID patients. CONCLUSIONS: The clinical manifestations of NIID exhibit significant variability, usually leading to misdiagnosis. Our results provided new imaging perspectives for accurately diagnosing and exploring this disease's neuropathological mechanisms.

Perspective on Lewis Acid-Base Interactions in Emerging Batteries.

Lewis acid-base interactions are common in chemical processes presented in diverse applications, such as synthesis, catalysis, batteries, semiconductors, and solar cells. The Lewis acid-base interactions allow precise tuning of material properties from the molecular level to more aggregated and organized structures. This review will focus on the origin, development, and prospects of applying Lewis acid-base interactions for the materials design and mechanism understanding in the advancement of battery materials and chemistries. The covered topics relate to aqueous batteries, lithium-ion batteries, solid-state batteries, alkali metal-sulfur batteries, and alkali metal-oxygen batteries. In this review, the Lewis acid-base theories will be first introduced. Thereafter the application strategies for Lewis acid-base interactions in solid-state and liquid-based batteries will be introduced from the aspects of liquid electrolyte, solid polymer electrolyte, metal anodes, and high-capacity cathodes. The underlying mechanism is highlighted in regard to ion transport, electrochemical stability, mechanical property, reaction kinetics, dendrite growth, corrosion, and so on. Last but not least, perspectives on the future directions related to Lewis acid-base interactions for next-generation batteries are like to be shared.

A lateral flow assay strip for simultaneous detection of miRNA and exosomes in liver cancer.

By employing an aptamer as the bridge and combining catalytic hairpin assembly with the Au aggregation amplification effect, a lateral flow assay (LFA) is designed for simultaneous detection of liver cancer-associated miRNA and exosomes. The LFA can differentiate between liver cancer patients and healthy individuals with simple operation and high accuracy.

Atomic-Layer IrOx Enabling Ligand Effect Boosts Water Oxidation Electrocatalysis.

An in situ formed IrOx (x ≤ 2) layer driven by anodic bias serves as the essential active site of Ir-based materials for oxygen evolution reaction (OER) electrocatalysis. Once being confined to atomic thickness, such an IrOx layer possesses both a favorable ligand effect and maximized active Ir sites with a lower O-coordination number. However, limited by a poor understanding of surface reconstruction dynamics, obtaining atomic layers of IrOx remains experimentally challenging. Herein, we report an idea of material design using intermetallic IrVMn nanoparticles to induce in situ formation of an ultrathin IrOx layer (O-IrVMn/IrOx) to enable the ligand effect for achieving superior OER electrocatalysis. Theoretical calculations predict that a strong electronic interaction originating from an orderly atomic arrangement can effectively hamper the excessive leaching of transition metals, minimizing vacancies for oxygen coordination. Linear X-ray absorption near edge spectra analysis, extended X-ray absorption fine structure fitting outcomes, and X-ray photoelectron spectroscopy collectively confirm that Ir is present in lower oxidation states in O-IrVMn/IrOx due to the presence of unsaturated O-coordination. Consequently, the O-IrVMn/IrOx delivers excellent acidic OER performances with an overpotential of only 279 mV at 10 mA cm-2 and a high mass activity of 2.3 A mg-1 at 1.53 V (vs RHE), exceeding most Ir-based catalysts reported. Moreover, O-IrVMn/IrOx also showed excellent catalytic stability with only 0.05 at. % Ir dissolution under electrochemical oxidation, much lower than that of disordered D-IrVMn/IrOx (0.20 at. %). Density functional theory calculations unravel that the intensified ligand effect optimizes the adsorption energies of multiple intermediates involved in the OER and stabilizes the as-formed catalytic IrOx layer.

Evaluation of Major Physical and Mechanical Properties of Trembling Aspen Lumber.

Trembling aspen (Populus tremuloides) is one of the major species within Populus, a predominant genus of hardwoods in North America. However, its utilization has been limited to pulp and paper or wood-based composite boards. This study aimed at evaluating the major physical and mechanical properties of trembling aspen lumber, with an ultimate objective of using this species to produce engineered wood products (EWPs). The testing materials consisted of 2 × 4 (38 mm × 89 mm) trembling aspen lumber pieces in lengths of 8, 10, and 12 feet (2.44, 3.05, and 3.66 m) with two visual grades, select structural (SS) and No. 2. Machine Stress-Rated (MSR), and longitudinal stress wave (LSW), edgewise third-point bending (EWB), and axial tension tests were conducted on the lumber. It was found that, (1) by increasing the maximum knot size by a half-inch from one-quarter inch, the minimum modulus of elasticity (MOE) measured using the MSR, the mean, and the fifth-percentile ultimate tensile strength (UTS) decreased by about 8.8%, 20.1%, and 29.8%, respectively. (2) Approximately 44% of the trembling aspen lumber met the 1450f-1.3E grade for MSR lumber, and 62% qualified for the 1200f-1.2E grade. (3) There was a great potential for manufacturing cross-laminated timber (CLT) of grade E3, with a rejection rate of about 29%. (4) The mean UTS and MOE values of the SS-grade trembling aspen lumber were 22.88 MPa and 9519 MPa, respectively, being 25.5% and 11.3% lower than that of Spruce-Pine-Fir (S-P-F) lumber. The fifth-percentile UTS and MOE values were 11.57 MPa and 7404 MPa, respectively, marking a decrease of 13.3% and 1.5% compared to the S-P-F lumber. (5) The oven-dried specific gravity (SG) of the trembling aspen wood was 0.40, which was about 3.5% larger than the value provided in the Wood Handbook.

A modified HSV-1 oncolytic virus reconciles antiviral and antitumor immunity via promoting IFNß expression and inhibiting PKR.

Type I interferon (IFN-I) is a potent immune modulator intricately involved in regulating tumor immunity. Meanwhile, the integrity of the IFN-I signaling pathway is essential for radiotherapy, chemotherapy, targeted therapy, and immunotherapy. However, the clinical application of IFN-I remains challenging due to its non-specific cytotoxicity and limited half-life. To overcome these limitations, we developed a gene delivery platform, CRISPR-V, enabling the rapid creation of novel HSV-1 oncolytic viruses. Utilizing this platform, we created an oncolytic virus, OVH-IFNß, in which the IFNß gene was incorporated into the HSV-1 genome. However, exogenous IFNß expression significantly inhibited OVH-IFNß replication. Through transcriptome data analyses, we identified several ISG genes inhibiting OVH-IFNß replication. By gene knockout and functional studies of the downstream effectors, we confirmed the prominent antiviral activities of protein kinase R (PKR). To balance the antitumor and antiviral immunity of IFNß, we developed a novel HSV-1 oncolytic virus, OVH-IFNß-iPKR, which can express IFNß while inhibiting PKR, leading to a potent antitumor immunity while reducing the antiviral capacity of IFNß. OVH-IFNß-iPKR shows a strong ability to induce immunogenic cell death and activate tumor-specific CD8+ T cells, leading to de novo immune responses and providing a novel strategy for tumor immunotherapy.

Expanding the clinical application of OPM-MEG using an effective automatic suppression method for the dental brace metal artifact.

Optically pumped magnetometer magnetoencephalography (OPM-MEG) holds significant promise for clinical functional brain imaging due to its superior spatiotemporal resolution. However, effectively suppressing metallic artifacts, particularly from devices such as orthodontic braces and vagal nerve stimulators remains a major challenge, hindering the wider clinical application of wearable OPM-MEG devices. A comprehensive analysis of metal artifact characteristics from time, frequency, and time-frequency perspectives was conducted for the first time using an OPM-MEG device in clinical medicine. This study focused on patients with metal orthodontics, examining the modulation of metal artifacts by breath and head movement, the incomplete regular sub-Gaussian distribution, and the high absolute power ratio in the 0.5-8 Hz band. The existing metal artifact suppression algorithms applied to SQUID-MEG, such as fast independent component analysis (FastICA), information maximization (Infomax), and algorithms for multiple unknown signal extraction (AMUSE), exhibit limited efficacy. Consequently, this study introduced the second-order blind identification (SOBI) algorithm, which utilized multiple time delays for the component separation of OPM-MEG measurement signals. We modified the time delays of the SOBI method to improve its efficacy in separating artifact components, particularly those in the ultralow frequency range. This approach employs the frequency-domain absolute power ratio, root mean square (RMS) value, and mutual information methods to automate the artifact component screening process. The effectiveness of this method was validated through simulation experiments involving four subjects in both resting and evoked experiments. In addition, the proposed method was also validated by the actual OPM-MEG evoked experiments of three subjects. Comparative analyses were conducted against the FastICA, Infomax, and AMUSE algorithms. Evaluation metrics included normalized mean square error, normalized delta band power error, RMS error, and signal-to-noise ratio, demonstrating that the proposed method provides optimal suppression of metal artifacts. This advancement holds promise for enhancing data quality and expanding the clinical applications of OPM-MEG.

Mass measurement under medium vacuum in optically levitated nanoparticles based on Maxwell speed distribution law.

As one of the directions of optical levitation technology, the mass measurement of micro-nano particles has always been a research hotspot in extremely weak mechanical measurements. When nanoscale particles are trapped in an optical trap, parameters such as density, diameter, and shape are unknown. Here we propose what we believe to be a new method to measure mass by fitting particle motion information to the Maxwell speed distribution law, with an accuracy better than 7% at 10 mbar. This method has the characteristics of requiring no external driving force, no precise natural frequency, no prior information such as density, and non-destructive testing within the medium vacuum range. With the increasing iterations, the uncertainty of mass measurement is reduced, and the accuracy of mass measurement of levitated particles is verified under multiple air pressures. It provides what we believe is a new method for the future non-destructive testing of nanoscale particles, and provides an apparently new way for the sensing measurement and metrology application fields of levitation dynamics systems.

Lanthanide-regulating Ru-O covalency optimizes acidic oxygen evolution electrocatalysis.

Precisely modulating the Ru-O covalency in RuOx for enhanced stability in proton exchange membrane water electrolysis is highly desired. However, transition metals with d-valence electrons, which were doped into or alloyed with RuOx, are inherently susceptible to the influence of coordination environment, making it challenging to modulate the Ru-O covalency in a precise and continuous manner. Here, we first deduce that the introduction of lanthanide with gradually changing electronic configurations can continuously modulate the Ru-O covalency owing to the shielding effect of 5s/5p orbitals. Theoretical calculations confirm that the durability of Ln-RuOx following a volcanic trend as a function of Ru-O covalency. Among various Ln-RuOx, Er-RuOx is identified as the optimal catalyst and possesses a stability 35.5 times higher than that of RuO2. Particularly, the Er-RuOx-based device requires only 1.837 V to reach 3 A cm-2 and shows a long-term stability at 500 mA cm-2 for 100 h with a degradation rate of mere 37 µV h-1.

Radioactive iodine therapy for thyroid cancer coexisting with Hashimoto's thyroiditis: a systematic review and meta-analysis.

OBJECTIVES: To investigate the clinical character of differentiated thyroid cancer (DTC) coexisting with Hashimoto's thyroiditis (HT) and provide state-of-art evidence for personalized radioactive iodine-131 therapy (RAIT) for patients coexisting with HT. METHODS: From January 2000 to January 2023, PubMed, Embase, and Web of Science databases were searched for relevant original articles that published in English on the RAIT efficacy for DTC with HT. RevMan 5.4 and Stata 17.0 were used for data analysis. RESULTS: Eleven studies involving 16 605 DTC patients (3321 with HT) were included. HT was more frequent in female (OR: 2.90, 95% confidence interval [CI]: 1.77-4.76, P < .00001). The size of tumour (MD: -0.20, 95% CI: -0.30 to -0.11), extrathyroidal extension rate (OR: 0.77, 95% CI: 0.67-0.90), and metastasis rate (OR: 0.18, 95% CI: 0.08-0.41) were less in HT, but tumour, node, metastasis (TNM) stage had no significant difference among HT and non-HT group. Disease-free survival (DFS) rate (OR: 1.96, 95% CI: 1.57-2.44, P < .00001), 5-year DFS (OR: 1.73, 95% CI: 1.04-2.89, P = .04), and 10-year DFS (OR: 1.56, 95% CI: 1.17-2.09, P = .003) were higher in HT group. The recurrent (OR: 0.62, 95% CI: 0.45-0.83, P = .002), RAIT dosage (MD = -38.71, 95% CI: -60.86 to -16.56, P = .0006), and treatment (MD: -0.13, 95% CI: -0.22 to -0.03, P = .008) were less in HT group. CONCLUSIONS: DTC coexisting with HT was associated with less invasion. DFS of HT group was higher than non-HT group after RAIT. Low-dose treatment did not impair the efficacy of RAIT in DTC with HT. ADVANCES IN KNOWLEDGE: Hashimoto's thyroiditis is a risk for DTC, but it minimalizes the progression of cancer and enhance the efficacy of RAIT, which should be considered in personalizing RAIT.

A polysaccharide PRCP from Rosa cymosa Tratt fruit: Structural characteristics and immunomodulatory effects via MAPK pathway modulation in vitro.

The Rosa cymosa Tratt, an herbal plant from the Rosaceae family, has historically been valued in China for its medicinal and edible properties. In this study, a novel polysaccharide from R. cymosa fruit, termed PRCP (purified R. cymosa polysaccharide), was isolated using water extraction, decolorization, deproteinization, and ion-exchange chromatography. The structural characteristics of PRCP were investigated using monosaccharide composition analysis, methylation, GPC, FTIR, CD, and NMR spectroscopy. The immunomodulatory effect and potential mechanism of PRCP were evaluated in vitro using a macrophage cell model. Results indicated that PRCP (37.28 kDa) is a highly branched polysaccharide (72.61 %) primarily composed of arabinogalactan, rhamnogalacturonan, and galactoglucan domains with 13 types of glycosidic linkage fragments. Furthermore, PRCP appears to modulate immunomodulatory effects by influencing the phosphorylation of P38 and JNK proteins in the MAPK pathway. Collectively, these findings highlight the potential of PRCP as a promising natural functional food ingredient for immunostimulation.

A novel strategy for detoxification of deoxynivalenol via modification of both toxic groups.

Deoxynivalenol (DON) is the most abundant mycotoxin in cereal crops and derived foods and is of great concern in agriculture. Bioremediation strategies have long been sought to minimize the impact of mycotoxin contamination, but few direct and effective enzyme-catalyzed detoxification methods are currently available. In this study, we established a multi-enzymatic cascade reaction and successfully achieved detoxification at double sites: glutathionylation for the C-12,13 epoxide group and epimerization for the C-3 hydroxyl group. This yielded novel derivatives of DON, 3-epi-DON-13-glutathione (3-epi-DON-13-GSH) as well as its by-product, 3-keto-DON-13-GSH, for which precise structures were validated via liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS) and nuclear magnetic resonance (NMR) spectroscopy. Both cell viability and DNA synthesis assays demonstrated dramatically decreased cytotoxicity of the double-site modified product 3-epi-DON-13-GSH. These findings provide a promising and urgently needed novel method for addressing the problem of DON contamination in agricultural and industrial settings.

Machine learning-based model for predicting outcomes in cerebral hemorrhage patients with leukemia.

BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) in leukemia patients progresses rapidly with high mortality. Limited data are available on imaging studies in this population. The study aims to develop prediction models for 7-day and short-term mortality risk based on the non-contrast computed tomography (NCCT) image features. METHODS: The NCCT image features of ICH in 135 leukemia patients between 2007-2023 were retrospectively extracted using manual assessment and radiomics methods. After multiple imputation of missing laboratory data, univariate logistic regression and least absolute shrinkage and selection operator (LASSO) were used for feature selection. Random forest models were built with comprehensive evaluation and ranking of feature importance. RESULT: 135 and 129 patients were included in the studies for 7-day and short-term prognostic models, respectively. The median age of all enrolled patients was 35 years, and there were 86 male patients (63.7 %). Clinical models (validation: AUC [area under the curve] = 0.78, AUPRC [area under the precision-recall curve] = 0.73; AUC = 0.84, AUPRC = 0.86), radiomics models (validation: AUC = 0.82, AUPRC = 0.78; AUC = 0.75, AUPRC = 0.77), and the combined models (validation: AUC = 0.84, AUPRC = 0.83; AUC = 0.87, AUPRC = 0.89) predicted 7-day and short-term mortality with good predictive efficacy. Clinical decision curve analysis showed that the combined models predicted 7-day and 30-day risk of death would be more beneficial than other models. Shape features contributed significantly more than semantic features in both radiomics models and combined models (93.3 %, 52.1 %, as well as 85.2 %,37.4 %, respectively) for 7-day and 30-day mortality. CONCLUSIONS: Combined models constructed based on NCCT perform well in predicting the risk of 7-day and short-term mortality in ICH patients with leukemia. Shape features extracted by radiomics are important markers for modeling the prognosis.

Source localization comparison and combination of OPM-MEG and fMRI to detect sensorimotor cortex responses.

BACKGROUND AND OBJECTIVES: The exploration of various neuroimaging techniques have become focal points within the field of neuroscience research. Magnetoencephalography based on optically pumped magnetometers (OPM-MEG) has shown significant potential to be the next generation of functional neuroimaging with the advantages of high signal intensity and flexible sensor arrangement. In this study, we constructed a 31-channel OPM-MEG system and performed a preliminary comparison of the temporal and spatial relationship between magnetic responses measured by OPM-MEG and blood-oxygen-level-dependent signals detected by functional magnetic resonance imaging (fMRI) during a grasping task. METHODS: For OPM-MEG, the ß-band (15-30 Hz) oscillatory activities can be reliably detected across multiple subjects and multiple session runs. To effectively localize the inhibitory oscillatory activities, a source power-spectrum ratio-based imaging method was proposed. This approach was compared with conventional source imaging methods, such as minimum norm-type and beamformer methods, and was applied in OPM-MEG source analysis. Subsequently, the spatial and temporal responses at the source-level between OPM-MEG and fMRI were analyzed. RESULTS: The effectiveness of the proposed method was confirmed through simulations compared to benchmark methods. Our demonstration revealed an average spatial separation of 10.57 ± 4.41 mm between the localization results of OPM-MEG and fMRI across four subjects. Furthermore, the fMRI-constrained OPM-MEG localization results indicated a more focused imaging extent. CONCLUSIONS: Taken together, the performance exhibited by OPM-MEG positions it as a potential instrument for functional surgery assessment.

Deep Learning Models of Multi-Scale Lesion Perception Attention Networks for Diagnosis and Staging of Pneumoconiosis: A Comparative Study with Radiologists.

Accurate prediction of pneumoconiosis is essential for individualized early prevention and treatment. However, the different manifestations and high heterogeneity among radiologists make it difficult to diagnose and stage pneumoconiosis accurately. Here, based on DR images collected from two centers, a novel deep learning model, namely Multi-scale Lesion-aware Attention Networks (MLANet), is proposed for diagnosis of pneumoconiosis, staging of pneumoconiosis, and screening of stage I pneumoconiosis. A series of indicators including area under the receiver operating characteristic curve, accuracy, recall, precision, and F1 score were used to comprehensively evaluate the performance of the model. The results show that the MLANet model can effectively improve the consistency and efficiency of pneumoconiosis diagnosis. The accuracy of the MLANet model for pneumoconiosis diagnosis on the internal test set, external validation set, and prospective test set reached 97.87%, 98.03%, and 95.40%, respectively, which was close to the level of qualified radiologists. Moreover, the model can effectively screen stage I pneumoconiosis with an accuracy of 97.16%, a recall of 98.25, a precision of 93.42%, and an F1 score of 95.59%, respectively. The built model performs better than the other four classification models. It is expected to be applied in clinical work to realize the automated diagnosis of pneumoconiosis digital chest radiographs, which is of great significance for individualized early prevention and treatment.

The Masquelet induced membrane technique with PRP-FG-nHA/PA66 scaffold can heal a rat large femoral bone defect.

BACKGROUND: Masquelet membrane induction technology is one of the treatment strategies for large bone defect (LBD). However, the angiogenesis ability of induced membrane decreases with time and autologous bone grafting is associated with donor site morbidity. This study investigates if the PRP-FG-nHA/PA66 scaffold can be used as a spacer instead of PMMA to improve the angiogenesis ability of induced membrane and reduce the amount of autologous bone graft. METHODS: Platelet rich plasma (PRP) was prepared and PRP-FG-nHA/PA66 scaffold was synthesized and observed. The sustained release of VEGFA and porosity of the scaffold were analyzed. We established a femur LBD model in male SD rats. 55 rats were randomly divided into four groups depending on the spacer filled in the defect area. "Defect only" group (n = 10), "PMMA" group (n = 15), "PRP-nHA/PA66" group (n = 15) and "PRP-FG-nHA/PA66" group (n = 15 ). At 6 weeks, the spacers were removed and the defects were grafted. The induced membrane and bone were collected and stained. The bone formation was detected by micro-CT and the callus union was scored on a three point system. RESULTS: The PRP-FG-nHA/PA66 scaffold was porosity and could maintain a high concentration of VEGFA after 30 days of preparation. The induced membrane in PRP-FG-nHA/PA66 group was thinner than PMMA, but the vessel density was higher.The weight of autogenous bone grafted in PRP-FG-nHA/PA66 group was significantly smaller than that of PMMA group. In PRP-FG-nHA/PA66 group, the bone defect was morphologically repaired. CONCLUSION: The study showed that PRP-FG-nHA/PA66 scaffold can significantly reduce the amount of autologous bone graft, and can achieve similar bone defect repair effect as PMMA. Our findings provide some reference and theoretical support for the treatment of large segmental bone defects in humans.

The influence of COVID-19 on intertemporal choices in the health and economy domains.

Background: With the spread of COVID-19, concerns regarding its adverse effects have arisen. Based on affect regulation theory and construal level theory, this study explored how COVID-19 affects intertemporal choice in the health and economy domains, self-other differences for intertemporal choice were also inspected. The study examined whether psychological safety can moderate the relationship between COVID-19 and intertemporal choice. Methods: A 2 (COVID-19 status: pre-COVID-19, during-COVID-19) × 2 (decision maker role: decision for self, decision for others) × 2 (domain: health, economy) three-factor hybrid experiment was employed. Results: (1) Individuals in during-COVID-19 condition preferred more immediate options. (2) Delayed options were preferred more in the health domain. Preference for immediate money options enhanced during than before COVID-19. However, COVID-19 status did not affect choices related to health. (3) Delayed options were preferred more when making intertemporal choices for others than for oneself under the pre-COVID-19 condition. Self-other differences for intertemporal choice disappeared during COVID-19. (4) Psychological safety moderated the effect of COVID-19 on intertemporal choice. Conclusions: During COVID-19, individuals' impulsive preference of intertemporal choice increased. COVID-19 affected intertemporal choice regarding economy and the self-other differences for intertemporal choice. Psychological safety could buffer the effect of COVID-19 on intertemporal choice. Value: This study can provide empirical evidence to affect regulation theory and level of explanation theory as well as guide individuals in making scientific decisions in health and economic domains under public health emergencies.